{
 "nbformat": 4,
 "nbformat_minor": 0,
 "metadata": {
  "colab": {
   "name": "basic_example.ipynb",
   "provenance": [],
   "collapsed_sections": []
  },
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3"
  },
  "language_info": {
   "name": "python"
  },
  "accelerator": "GPU"
 },
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lqRGAV4PrwqL"
   },
   "source": [
    "# Introduction to BlenderProc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "y-i21RQVPngI"
   },
   "source": [
    "Note: This notebook makes use of the basic example which is available under `examples/basic`\n",
    "\n",
    "In this notebook, we will see how can we quickly set up the BlenderProc environment inside Google Colab and how can we generate photorealistic data which can later be used for many different applications."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pzZINFtAQ19Z"
   },
   "source": [
    "We firstly clone the official BlenderProc repo (repository) from GitHub using Git"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "VvYDI2DLsCbr",
    "outputId": "0f7d89a0-e446-4c50-c94e-3ad5adc1ee47"
   },
   "source": [
    "# git clone the BlenderProc repo\n",
    "!git clone https://github.com/DLR-RM/BlenderProc.git"
   ],
   "execution_count": 1,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "fatal: destination path 'BlenderProc' already exists and is not an empty directory.\n"
     ],
     "name": "stdout"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G0Tn2DQnRJcz"
   },
   "source": [
    "We change our present working directory to the BlenderProc repo"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "bK0iezmrs7FX",
    "outputId": "12efa98f-ce54-474a-a606-a80581bd4218"
   },
   "source": [
    " # change directory to BlenderProc\n",
    " %cd \"BlenderProc\""
   ],
   "execution_count": 2,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "/content/BlenderProc\n"
     ],
     "name": "stdout"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G_XZ7SpWRan2"
   },
   "source": [
    "We view the present working directory to make sure we are inside the BlenderProc repo"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Plk6OzwJ6WVx",
    "outputId": "4dd4ecc2-3ed9-4747-a013-4f3481da33b6"
   },
   "source": [
    "# present working directory \n",
    "!pwd"
   ],
   "execution_count": 3,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "/content/BlenderProc\n"
     ],
     "name": "stdout"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BXlzLifCR80c"
   },
   "source": [
    "In order to run BlenderProc inside Google Colab, we first have to update the `LD_PRELOAD` environment variable"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "BMFdNLxNBO0R"
   },
   "source": [
    "import os\n",
    "\n",
    "# updating the LD_PRELOAD env variable\n",
    "os.environ[\"LD_PRELOAD\"] = \"/usr/lib/x86_64-linux-gnu/libtcmalloc_minimal.so.4.3.0\""
   ],
   "execution_count": 4,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "56WrQIdaSepi"
   },
   "source": [
    "Then, we update the `blender_install_path` config variable in the `config.yaml` file inside the basic example. The reason for making this change is that we want to specify the custom Blender install path as an argument in the next step. "
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "id": "vjLnTYq2y8TU"
   },
   "source": [
    "import yaml\n",
    "\n",
    "# load the basic example config file\n",
    "with open(\"examples/basics/basic/config.yaml\", \"r\") as f:\n",
    "  config = yaml.safe_load(f)\n",
    "\n",
    "# update the \"blender_install_path\" variable with the correct Blender installation path \n",
    "config[\"setup\"][\"blender_install_path\"] = \"<args:3>\"\n",
    "\n",
    "# write the basic example config file after making the change\n",
    "with open(\"examples/basics/basic/config.yaml\", \"w\") as f:\n",
    "  yaml.dump(config, f)"
   ],
   "execution_count": 5,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1Lz4nvzETWXU"
   },
   "source": [
    "Finally, we run the BlenderProc program using the `run.py` file along with required command line arguments. The first argument specifies the location of the YAML config file. The second argument corresponds to the camera pose file. In this case, we have specified two camera poses in the `examples/basics/basic/camera_positions` file. The third argument correponds to the output directory where our generated data will be stored. The fourth argument corresponds to the custom Blender install path which will be installed in the current directory by the `run.py` file."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jVZTximT08tN",
    "outputId": "e416af63-9a80-40c2-88a9-702cad788553"
   },
   "source": [
    "# run the BlenderProc basic example\n",
    "!python run.py examples/basics/basic/config.yaml examples/resources/camera_positions examples/resources/scene.obj examples/basics/basic/output ./"
   ],
   "execution_count": 6,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "Parsing config 'examples/basic/config.yaml'\n",
      "Filling placeholder <args:2> at modules/(main.Initializer)/config/global/output_dir: examples/basic/output\n",
      "Filling placeholder <args:1> at modules/(loader.ObjectLoader)/config/path: examples/basic/scene.obj\n",
      "Filling placeholder <args:0> at modules/(camera.CameraLoader)/config/path: examples/basic/camera_positions\n",
      "Filling placeholder <args:3> at setup/blender_install_path: ./\n",
      "Successfully finished parsing \n",
      "Using blender in ./blender-2.91.0-linux64\n",
      "Looking in links: /tmp/tmp41gk1gta\n",
      "Requirement already satisfied: setuptools in ./blender-2.91.0-linux64/2.91/python/lib/python3.7/site-packages (41.2.0)\n",
      "Requirement already satisfied: pip in ./blender-2.91.0-linux64/2.91/python/lib/python3.7/site-packages (21.1)\n",
      "\u001B[33mWARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: /content/BlenderProc/blender-2.91.0-linux64/2.91/python/include/python3.7m/UNKNOWN\n",
      "sysconfig: /content/BlenderProc/blender-2.91.0-linux64/2.91/python/include/python3.7m\u001B[0m\n",
      "\u001B[33mWARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\u001B[0m\n",
      "Requirement already satisfied: pip in ./blender-2.91.0-linux64/2.91/python/lib/python3.7/site-packages (21.1)\n",
      "\u001B[33mWARNING: Value for scheme.headers does not match. Please report this to <https://github.com/pypa/pip/issues/9617>\n",
      "distutils: /content/BlenderProc/blender-2.91.0-linux64/2.91/python/include/python3.7m/UNKNOWN\n",
      "sysconfig: /content/BlenderProc/blender-2.91.0-linux64/2.91/python/include/python3.7m\u001B[0m\n",
      "\u001B[33mWARNING: Additional context:\n",
      "user = False\n",
      "home = None\n",
      "root = None\n",
      "prefix = None\u001B[0m\n",
      "\u001B[33mWARNING: Running pip as root will break packages and permissions. You should install packages reliably by using venv: https://pip.pypa.io/warnings/venv\u001B[0m\n",
      "pyyaml:5.1.2 was installed: True\n",
      "Using temporary directory: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5\n",
      "Blender 2.91.0 (hash 0f45cab862b8 built 2020-11-25 08:51:08)\n",
      "ALSA lib confmisc.c:767:(parse_card) cannot find card '0'\n",
      "ALSA lib conf.c:4528:(_snd_config_evaluate) function snd_func_card_driver returned error: No such file or directory\n",
      "ALSA lib confmisc.c:392:(snd_func_concat) error evaluating strings\n",
      "ALSA lib conf.c:4528:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory\n",
      "ALSA lib confmisc.c:1246:(snd_func_refer) error evaluating name\n",
      "ALSA lib conf.c:4528:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory\n",
      "ALSA lib conf.c:5007:(snd_config_expand) Evaluate error: No such file or directory\n",
      "ALSA lib pcm.c:2495:(snd_pcm_open_noupdate) Unknown PCM default\n",
      "found bundled python: /content/BlenderProc/blender-2.91.0-linux64/2.91/python\n",
      "Info: Deleted 3 object(s)\n",
      "Info: Deleted 3 object(s)\n",
      "#### Start - Initializing module main.Initializer ####\n",
      "#### Finished - Initializing module main.Initializer (took 0.007 seconds) ####\n",
      "#### Start - Initializing module loader.ObjectLoader ####\n",
      "#### Finished - Initializing module loader.ObjectLoader (took 0.005 seconds) ####\n",
      "#### Start - Initializing module lighting.LightLoader ####\n",
      "#### Finished - Initializing module lighting.LightLoader (took 0.005 seconds) ####\n",
      "#### Start - Initializing module camera.CameraLoader ####\n",
      "#### Finished - Initializing module camera.CameraLoader (took 0.001 seconds) ####\n",
      "#### Start - Initializing module renderer.RgbRenderer ####\n",
      "#### Finished - Initializing module renderer.RgbRenderer (took 0.021 seconds) ####\n",
      "#### Start - Initializing module writer.Hdf5Writer ####\n",
      "#### Start - Initializing module postprocessing.TrimRedundantChannels ####\n",
      "#### Finished - Initializing module postprocessing.TrimRedundantChannels (took 0.001 seconds) ####\n",
      "#### Finished - Initializing module writer.Hdf5Writer (took 0.051 seconds) ####\n",
      "#### Start - Running blender pipeline ####\n",
      "#### Start - Running module Initializer ####\n",
      "Device Tesla K80 of type CUDA found and used.\n",
      "#### Finished - Running module Initializer (took 0.033 seconds) ####\n",
      "#### Start - Running module ObjectLoaderModule ####\n",
      "(  0.0000 sec |   0.0000 sec) Importing OBJ '/content/BlenderProc/examples/basic/scene.obj'...\n",
      "  (  0.0001 sec |   0.0001 sec) Parsing OBJ file...\n",
      "    (  0.0148 sec |   0.0147 sec) Done, loading materials and images...\n",
      "    (  0.0177 sec |   0.0175 sec) Done, building geometries (verts:841 faces:854 materials: 9 smoothgroups:0) ...\n",
      "    (  0.0313 sec |   0.0312 sec) Done.\n",
      "  (  0.0314 sec |   0.0313 sec) Finished importing: '/content/BlenderProc/examples/basic/scene.obj'\n",
      "Progress: 100.00%\n",
      "\n",
      "#### Finished - Running module ObjectLoaderModule (took 0.034 seconds) ####\n",
      "#### Start - Running module LightLoader ####\n",
      "#### Finished - Running module LightLoader (took 0.000 seconds) ####\n",
      "#### Start - Running module CameraLoader ####\n",
      "#### Finished - Running module CameraLoader (took 0.001 seconds) ####\n",
      "#### Start - Running module RgbRenderer ####\n",
      "Resolution: 512, 512\n",
      "Fra:0 Mem:22.09M (Peak 22.37M) | Time:00:00.05 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Cube\n",
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      "Fra:0 Mem:22.30M (Peak 22.53M) | Time:00:00.05 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Initializing\n",
      "Fra:0 Mem:21.59M (Peak 22.53M) | Time:00:00.05 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Waiting for render to start\n",
      "Fra:0 Mem:21.59M (Peak 22.53M) | Time:00:00.05 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Loading render kernels (may take a few minutes the first time)\n",
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      "Fra:0 Mem:50.69M (Peak 50.69M) | Time:00:07.58 | Compositing | Tile 4-4\n",
      "Fra:0 Mem:50.69M (Peak 50.69M) | Time:00:07.60 | Compositing | Tile 1-4\n",
      "Fra:0 Mem:50.69M (Peak 50.69M) | Time:00:07.61 | Compositing | Tile 2-4\n",
      "Fra:0 Mem:50.69M (Peak 50.69M) | Time:00:07.63 | Compositing | Tile 3-4\n",
      "Fra:0 Mem:50.69M (Peak 50.69M) | Time:00:07.65 | Compositing | Tile 4-4\n",
      "Fra:0 Mem:50.63M (Peak 50.69M) | Time:00:07.65 | Compositing | De-initializing execution\n",
      "Saved: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/distance_0000.exr\n",
      "Saved: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/normals_0000.exr\n",
      "Fra:0 Mem:26.63M (Peak 50.69M) | Time:00:07.74 | Sce: Scene Ve:0 Fa:0 La:0\n",
      "Saved: '/dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/rgb_0000.png'\n",
      " Time: 00:08.10 (Saving: 00:00.36)\n",
      "\n",
      "Fra:1 Mem:22.34M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Cube\n",
      "Fra:1 Mem:22.34M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Cube.001\n",
      "Fra:1 Mem:22.34M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Icosphere\n",
      "Fra:1 Mem:22.36M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Icosphere.001\n",
      "Fra:1 Mem:22.37M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Icosphere.002\n",
      "Fra:1 Mem:22.39M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Suzanne\n",
      "Fra:1 Mem:22.51M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Cylinder\n",
      "Fra:1 Mem:22.53M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Cylinder.001\n",
      "Fra:1 Mem:22.54M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Synchronizing object | Cylinder.002\n",
      "Fra:1 Mem:22.55M (Peak 50.69M) | Time:00:00.04 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Initializing\n",
      "Fra:1 Mem:21.84M (Peak 50.69M) | Time:00:00.05 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Waiting for render to start\n",
      "Fra:1 Mem:21.84M (Peak 50.69M) | Time:00:00.05 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Loading render kernels (may take a few minutes the first time)\n",
      "Fra:1 Mem:21.84M (Peak 50.69M) | Time:00:00.07 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Updating Scene\n",
      "Fra:1 Mem:21.84M (Peak 50.69M) | Time:00:00.07 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Updating Shaders\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Updating Background\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Updating Camera\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Updating Meshes Flags\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Updating Objects\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.00M, Peak:0.00M | Scene, View Layer | Updating Objects | Copying Transformations to device\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.01M, Peak:0.01M | Scene, View Layer | Updating Objects | Applying Static Transformations\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.01M, Peak:0.01M | Scene, View Layer | Updating Particle Systems\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.01M, Peak:0.01M | Scene, View Layer | Updating Particle Systems | Copying Particles to device\n",
      "Fra:1 Mem:22.10M (Peak 50.69M) | Time:00:00.07 | Mem:0.01M, Peak:0.01M | Scene, View Layer | Updating Meshes\n",
      "Fra:1 Mem:22.12M (Peak 50.69M) | Time:00:00.07 | Mem:0.01M, Peak:0.01M | Scene, View Layer | Updating Mesh | Computing attributes\n",
      "Fra:1 Mem:22.18M (Peak 50.69M) | Time:00:00.07 | Mem:0.01M, Peak:0.01M | Scene, View Layer | Updating Mesh | Copying Attributes to device\n",
      "Fra:1 Mem:22.18M (Peak 50.69M) | Time:00:00.07 | Mem:0.06M, Peak:0.06M | Scene, View Layer | Updating Scene BVH | Building\n",
      "Fra:1 Mem:22.18M (Peak 50.69M) | Time:00:00.07 | Mem:0.06M, Peak:0.06M | Scene, View Layer | Updating Scene BVH | Building BVH\n",
      "Fra:1 Mem:22.27M (Peak 50.69M) | Time:00:00.08 | Mem:0.06M, Peak:0.06M | Scene, View Layer | Updating Scene BVH | Packing BVH triangles and strands\n",
      "Fra:1 Mem:22.35M (Peak 50.69M) | Time:00:00.08 | Mem:0.06M, Peak:0.06M | Scene, View Layer | Updating Scene BVH | Packing BVH nodes\n",
      "Fra:1 Mem:22.30M (Peak 50.69M) | Time:00:00.08 | Mem:0.06M, Peak:0.06M | Scene, View Layer | Updating Scene BVH | Copying BVH to device\n",
      "Fra:1 Mem:22.31M (Peak 50.69M) | Time:00:00.08 | Mem:0.19M, Peak:0.19M | Scene, View Layer | Updating Mesh | Computing normals\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.19M, Peak:0.19M | Scene, View Layer | Updating Mesh | Copying Mesh to device\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.30M, Peak:0.30M | Scene, View Layer | Updating Objects Flags\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.30M, Peak:0.30M | Scene, View Layer | Updating Images\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.30M, Peak:0.30M | Scene, View Layer | Updating Camera Volume\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.30M, Peak:0.30M | Scene, View Layer | Updating Lookup Tables\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.55M, Peak:0.55M | Scene, View Layer | Updating Lights\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.55M, Peak:0.55M | Scene, View Layer | Updating Lights | Computing distribution\n",
      "Fra:1 Mem:22.42M (Peak 50.69M) | Time:00:00.08 | Mem:0.55M, Peak:0.55M | Scene, View Layer | Updating Integrator\n",
      "Fra:1 Mem:23.68M (Peak 50.69M) | Time:00:00.08 | Mem:1.81M, Peak:1.81M | Scene, View Layer | Updating Film\n",
      "Fra:1 Mem:23.68M (Peak 50.69M) | Time:00:00.08 | Mem:1.56M, Peak:1.81M | Scene, View Layer | Updating Lookup Tables\n",
      "Fra:1 Mem:23.68M (Peak 50.69M) | Time:00:00.08 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Updating Baking\n",
      "Fra:1 Mem:23.68M (Peak 50.69M) | Time:00:00.08 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Updating Device | Writing constant memory\n",
      "Fra:1 Mem:23.68M (Peak 50.69M) | Time:00:00.08 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Updating Device | Writing constant memory | Compiling render kernels\n",
      "Fra:1 Mem:23.68M (Peak 50.69M) | Time:00:00.08 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Updating Device | Writing constant memory\n",
      "Fra:1 Mem:23.69M (Peak 50.69M) | Time:00:00.08 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 0/4 Tiles, Sample 0/350\n",
      "Fra:1 Mem:27.69M (Peak 50.69M) | Time:00:01.09 | Remaining:00:09.14 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 0/4 Tiles, Sample 136/350\n",
      "Fra:1 Mem:27.69M (Peak 50.69M) | Time:00:02.10 | Remaining:00:08.25 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 0/4 Tiles, Sample 272/350\n",
      "Fra:1 Mem:23.69M (Peak 50.69M) | Time:00:02.68 | Remaining:00:07.72 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 1/4 Tiles, Sample 350/350\n",
      "Fra:1 Mem:27.69M (Peak 50.69M) | Time:00:03.11 | Remaining:00:07.00 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 1/4 Tiles, Sample 70/350\n",
      "Fra:1 Mem:27.69M (Peak 50.69M) | Time:00:04.12 | Remaining:00:05.56 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 1/4 Tiles, Sample 236/350\n",
      "Fra:1 Mem:23.69M (Peak 50.69M) | Time:00:04.81 | Remaining:00:04.70 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 2/4 Tiles, Sample 350/350\n",
      "Fra:1 Mem:27.69M (Peak 50.69M) | Time:00:05.12 | Remaining:00:03.26 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 2/4 Tiles, Sample 148/350\n",
      "Fra:1 Mem:23.69M (Peak 50.69M) | Time:00:05.54 | Remaining:00:01.80 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 3/4 Tiles, Sample 350/350\n",
      "Fra:1 Mem:27.69M (Peak 50.69M) | Time:00:06.12 | Remaining:00:00.96 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 3/4 Tiles, Sample 156/350\n",
      "Fra:1 Mem:23.69M (Peak 50.69M) | Time:00:06.85 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Rendered 4/4 Tiles\n",
      "Fra:1 Mem:23.69M (Peak 50.69M) | Time:00:06.85 | Mem:1.82M, Peak:1.82M | Scene, View Layer | Finished\n",
      "Fra:1 Mem:21.63M (Peak 50.69M) | Time:00:06.92 | Compositing\n",
      "Fra:1 Mem:21.63M (Peak 50.69M) | Time:00:06.92 | Compositing | Determining resolution\n",
      "Fra:1 Mem:21.63M (Peak 50.69M) | Time:00:06.92 | Compositing | Initializing execution\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.76 | Compositing | Tile 1-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.76 | Compositing | Tile 2-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.76 | Compositing | Tile 3-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.76 | Compositing | Tile 4-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.77 | Compositing | Tile 1-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.77 | Compositing | Tile 2-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.77 | Compositing | Tile 3-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.77 | Compositing | Tile 4-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.79 | Compositing | Tile 1-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.80 | Compositing | Tile 2-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.82 | Compositing | Tile 3-4\n",
      "Fra:1 Mem:50.69M (Peak 50.69M) | Time:00:08.84 | Compositing | Tile 4-4\n",
      "Fra:1 Mem:50.63M (Peak 50.69M) | Time:00:08.84 | Compositing | De-initializing execution\n",
      "Saved: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/distance_0001.exr\n",
      "Saved: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/normals_0001.exr\n",
      "Fra:1 Mem:26.63M (Peak 50.69M) | Time:00:08.94 | Sce: Scene Ve:0 Fa:0 La:0\n",
      "Saved: '/dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/rgb_0001.png'\n",
      " Time: 00:09.03 (Saving: 00:00.09)\n",
      "\n",
      "#### Finished - Running module RgbRenderer (took 17.199 seconds) ####\n",
      "#### Start - Running module Hdf5Writer ####\n",
      "Merging data for frame 0 into /content/BlenderProc/examples/basic/output/0.hdf5\n",
      "Key: distance - shape: (512, 512) - dtype: float32 - path: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/distance_0000.exr\n",
      "Key: normals - shape: (512, 512, 3) - dtype: float32 - path: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/normals_0000.exr\n",
      "Key: colors - shape: (512, 512, 3) - dtype: uint8 - path: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/rgb_0000.png\n",
      "Merging data for frame 1 into /content/BlenderProc/examples/basic/output/1.hdf5\n",
      "Key: distance - shape: (512, 512) - dtype: float32 - path: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/distance_0001.exr\n",
      "Key: normals - shape: (512, 512, 3) - dtype: float32 - path: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/normals_0001.exr\n",
      "Key: colors - shape: (512, 512, 3) - dtype: uint8 - path: /dev/shm/blender_proc_4ac4ecace8ff4677b15f775c116299e5/rgb_0001.png\n",
      "#### Finished - Running module Hdf5Writer (took 0.398 seconds) ####\n",
      "#### Finished - Running blender pipeline (took 17.666 seconds) ####\n",
      "\n",
      "Blender quit\n",
      "Cleaning temporary directory\n"
     ],
     "name": "stdout"
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xbyP7EC4T9kc"
   },
   "source": [
    "We visualize the first rendered color, depth and normal image which corresponds to the `0.hdf5` file inside the `examples/basics/basic/output` folder"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 826
    },
    "id": "6PeHFCV2HbbA",
    "outputId": "ab8f05e1-b441-4026-a6f5-54c9dc5971a8"
   },
   "source": [
    "# visualize the generated data (0.hdf5)\n",
    "%run \"scripts/visHdf5Files.py\" \"examples/basics/basic/output/0.hdf5\""
   ],
   "execution_count": 7,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "examples/basic/output/0.hdf5 contains the following keys: <KeysViewHDF5 ['blender_proc_version', 'colors', 'colors_version', 'distance', 'distance_version', 'normals', 'normals_version']>\n"
     ],
     "name": "stdout"
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": [],
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": [],
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": [],
      "needs_background": "light"
     }
    }
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "fg72XDwWTbhf"
   },
   "source": [
    "We visualize the second rendered color, depth and normal image which corresponds to the `1.hdf5` file inside the `examples/basics/basic/output` folder"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 826
    },
    "id": "u0YuChqdzX2p",
    "outputId": "a4cb1b12-08f0-4ff5-b26f-75640f53e277"
   },
   "source": [
    "# visualize the generated data (1.hdf5)\n",
    "%run \"scripts/visHdf5Files.py\" \"examples/basics/basic/output/1.hdf5\""
   ],
   "execution_count": 8,
   "outputs": [
    {
     "output_type": "stream",
     "text": [
      "examples/basic/output/1.hdf5 contains the following keys: <KeysViewHDF5 ['blender_proc_version', 'colors', 'colors_version', 'distance', 'distance_version', 'normals', 'normals_version']>\n"
     ],
     "name": "stdout"
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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vYTz3zKFqQTAXsL3SjclgYZvADVHRuHEdoC6x2XAAmF5iGNfIR7He/TkwUeeY8ns5SKQjtWXZXL1yhaWlJRqNBvV6nbnGHF/88hd5+PBhZfvZtsNic57r164x15xn0O9l7ea6Lv6gz/bWBr3tDo1mi/nmAosLCywvL6Mav4jYtixWV1f58le+wmd/+7N0Op0jvf99QSBoBHRXumydbdNZ3Mb3/JgMSKZDbaBOTAgyqhnsd3ydXmIYh9MkSFOkqh5s3uO744Xz5/kDv/8PUKvVsC2LeqNBvV7Ddmz+xb/8F4RhmNWnVqtxbvU8169dw0K5ev06jm0T2U6cTsBxPWzbwZgIYyI6G2tsPn2M63k0Wgs0W0vUGnMANBpzfN/3fi9Xr1zh3/7GJ7l9+/aetIejggBqQVgL6S33EjLo4Nd8jOTaUwEb1FOoCWJR4UgYGhD7iaY4ecQwtTh82+cwTRRNX6Z7IGVU5+G5LjdfukE06NHutmm2FmgsL4FY3Hz5FS5dvMjde/doNltcuXyZK1eustBaQETwe9s0W01UBMf1EoFWsCxs10WDmEwMEWJF+IFPsPaUzsYzXLdGfb5FcyEmictXrvDRP/pR3njjDW7fuc2zZ8/obHfo9/tEUXT0pmAaa7DUo322Q3upzaDmYyxTrQK4xFpC4keIKWBIBPG35wuumhHDCPYr4Cdbkzls34iI8PK1KzQ94cn9tzFRxH1/wHzz32W+uUCtXufD3/dh3rl1m3Or52g0Gti2jYgw6Pc5e2YFy7JAFdu2cRyXMAqxRPC8OqlQWLaT+CxiX4Sq4vsD/EGfrbUnuLUa860lFlfO8sEPfZDv/u7vIghDutvbbGxssLa2xte+/jVu3b59gPdewbcCxjX0F/psnW3TXm7Tq/dRy8SCLbFvIVMUhJgI6sRSaw0P5/PUpLxKQpkAM2IYweEKR1n4psVZedh1WF1Z4d2vvYpGIcGgTxT4bDx+wJtf/xLv++APYNsON67fwPPq+L6PZVkxEQC2Ba2FVpJT/K5Px/MgtLBth1pjDhMZIhMRBiFRGBCFISYKiaL4exSFqAnxB32i6BmBP6C1tEKztUjN86i5LosLLa5evoglyu07dw6sTfLZGNcwaA3YOpOQwVyfyIqyWxteo8NjFmhNwIu1urzVkBFBwWwQRqYiDnqX6BkODlUd7XAEcrrCt+fqdd7/nnfRqNfxBz1A8AMfYwz3336T1QtXuHjtJWzHZmlpkbW1dUAIg4CNjXXOnV3Gth0ya4dY2GzHxbIsTBTR6bQxkcF2bJrNVpweQ+D7DPo9/H4/KVuxHYcw9Nlce4yJQuabC6Amc5A25+epeTX6g/6B3L86hkHTp73SYWtli95cj9A2IKVnlBPmNJxZU7Mh9SNUjfy5WWDNJcnxxcSYGmKYtjj3k42qdjwesnBsm/e+fpOzZ1YAsKxY1Q/DACtxGn7rq19k8cxZ5psLzM/P0ev1efjgIffvP2BpYZ7WQosoChHLRiwLE0YYVaIoot/v43kejuOyub3B2rOnLDRbtBYX8TwHr1ZnYXEJ54xLGAa0N9fo9bqgiuvVcFwPY6Kh/AhcuXKFj/zRP8qnPvUp7j24X0ne49wxaT9WW/HnfTorHTZXtujO9wjtMCsDKD6O3DERUAeoxf9jjaCsAlQ4GyWfcSntSTUlXhhSOLYpysMts8oksi2Lm9evcu3y5fi8CFgWCkRBiBIbw91Om29+5Xd47f0fojHXZGVlma3NLebn6rzy8nVsy4qdglFE4Ac4rofjOKhRXNfF81w8r0ZrYYErV69h2bGJYcKAzfU11p88Znn1HCtnVrEsC39wH8u2mG8uYid+CxKbHhUcx+Hll15iaWGBX/3/fo233n57tDVzmn7aumorfsOns7zN1soW281tQifEiCbOwOSi/LCeCnEqyxZoDdQjtZqKBZG/LjmROycjX/Jp946pIYYXBlPgTzgMlEnBsixeunqZ116+kan/lljYjovj1bHcGlG3h2psXz+49SZba0+4/tp7uXjtJtevX2N5cQ7Pc5P8wRjDYDDAq9Xp9/tYtoXrpl1Y42CpxDfh2DY4NqsXLuJ4NTrteBakPjfH4vIKqopl25nIxLMycT7p4Lu8ssL3fc/3cu/+fQaDQfV9J7EG20tdts5s0Wl2CNwAg2YyK+kN5Mkgk+uh7aCegkccm1DlPSzbCAVOkKLpUFAaJp+jmHpimC5reYa9wBLhxuULvP7yDWzbTmTCArGxbIvl1QssrKyytfGMW99+g36vzVxjju3OFm988dM8uX+Xl9/9flzPTXg0Fvog8BOPu9Dv9XA9FxNFeLU6IpI5K9UYjDFYtgUIC0vL+IMBQeDjui6NuXn6/T5ZLGYitKLxpF/c6RRL4MKF85xbXeXO3bukp0iuNLbh8bknrF1eJ2jEgUflvqqMuhLKKQpmQ/HKYk6pppFmWtI8NE8AJYKYVCOf+o1aTh0pPN/08tTDEuHyhXO8/vINXDce7Y2CioVlOyAW29vbPHvyFNer84Hv+X289h0fZK61iO242I6H7br0el1MFAu4qmKMod/rowpPHj7EmAhUiaKQwO+jxsSfZIrSmAgTRRhjsC2htbCYdSaTe0G7qmZr5eJvcWi2JgzheR6vvPxKRjpJUtRSnqw84UHzAb1ul2hgRpXBit/5yG+1wdQVbcQ+iZ2dhblZh0rzQnJl5m0LYZeMKzH1xHC0OAKpPXVMN4SIcHH1DO+5+RKu68ajKhZBENLv9QjDANdzWVha5tyly8w3F1Cj3Hjl3bz8rg9QazQ5e/k6zcXleHoxEfJU0AeDHoNBnwf37yTCazJJCwKfMAzjY4mAmyiKpyyT40p8zTBNPiRoqN7Hv+K/lli8fOMGjUYjO4fAs6U1Hiw+xIiBEHTToNsGyltCaJb7sDwLtBYTQhzKPKxFsX9UzGLlar23UIX0pibreFNvShwt9t540xJ/sFccRQDThbMrvOfVl3N+ASHwAzbXnuI25jjjOLiui+04LC+fwfM8br/zNmEYsnTmLFdefi3bbMUkEYj5eltisbm+xqM736ZR87h0LTZV4rI0IRMTax5WKtySCKegUcSg18egWJadbL0WE0gqnCNuAIHl5WUuXbzIm29+GxVlY2GD+8v3s/gD1ViJ146igcFqCjhSVOdJpx9jP4LaOcdivt+NnWvMOSlTbSfPZLsZCzvbMyM4cRrDtOyjtx8hO86aHyopAPOezc2rF6l56WoeC98PePrgFo7n0VxYyFZSWpYQ+ANs22Z5eYUwDPE8j1qtnuVpjMGkGgGp5mB4+uA2vX6bh3feor/dQY3JzkdRyNbaU9rrTwkCP9Mm/MBHE9IIoxBUESv2P+RNlVibSHUFTWYpwHEdzp45CwLtZps7Z+4SWEHSsEXXnvYNZsOgPS3Iu9qKaRi0HpNCJVRRk3wiRSODCQxRYIh8Q+RHRH5IOAgJ+/lPRDRIPn78MYHBhMknUibd3GrKNIbdXY3TOkqLgGtbNGo2nmPh2BauY+E5QmSU3iBiEBj8IMIPDaFJR5ojsC4OcYpUAM+Cmvpsrz+k0ahjOy6RCel32vQ6beqtRYLBgLn5eRzHRoAwCIiiiLn5eTbW13LViyP7RCyiMEItxSTtlAYzeW6N9tYGb339i8y35mktrTLXahH6fWqNOZruMt3tNo25FogQBfF+h1YSBwFA6ocwZvgMErNFRMGygXibNBFhZXmZ7lyX22fu4Nt+kkWq2Eum3QBoqOiWQQKQlsTTj25CNLn9Y7K+XHo0mdux4CrIT3HkfsNwTyGGA2fRdakTd7IpI4bdan/YYjRZ/pYlzNdsVhZqnF2ssdyqM9dwsC2r8GDTDhBFhjA09PyIZ5t9Hq/32dj28QNNHGKHhEMkhUUXXFE8W+lsPGGutUR9fpEgiFi9dJUnz9YQLPq9beYGDcz8fBLuLDnhjBdE2Y5LvQGWbWOJlWkNkgT/1+oNmgtLiCWERukHfXqPN2hvPOXMhStcufE6bq0eB0KJTb/XxXZsLJHkWM6jkMxcoJnBMZy6NIrtxCk10QjmzjS4f/4+Pas3MvmXV+mzQL1ICR6HhJsh1mUbCRNTJV0DkZumTP9Lbn5zVNAV0dzUZnZpSQ/NMUIaKbofTBkx7Ia9dfD929PV15TpwhJhcd7lpYstLpydo+451ate0y/JScexcRybet1luVXjxqUFur2AZ5t9bj/eZr0TYMx0akTj4NiwWEumIl2PzfWnIC71uRZPnzzCEjBRgGVbBP6AfnebWqNBvTEHxCq8l6yWtCwLx0l2GkkERJIvCohl0Vw6w/qzx5w5cwbHXabb7dJsLbK8egHbrWE5LmpMHP6sSq3ewPJqiAw1BVXNfBipLCqx+eIP+nFkZuDHMRG2Qzfs8/++8wk27a2EVTQ3rUluQiAemc3AEGwEhEGIzim2p9jnHcSSXLwEFTKtJdIZJY986pEK5H89Dytw4ohhbzhocyPP3otzLi9fanFpdZ6a51SkShOndRnNL32cjiUszHu05j0urc7z4Ok2bz3osLUdcBL4QYFuCAsuuJ5Dc+kctcY82+0t1p4+ptftUa/XULMYL402higM2W5vUq/ViaIaxiiO6xIEQVFrSrTfQt8Wi8XlM7RXL9GY8xh029Q8jzDosfnsEf3tNotnzuK6XuzLsJ1M4NXEsxJREGJMGGsWiYmlQBSFPLr7FvOtZeqNeSJVNFT6wRa/+OYv8VtPPhP7PEiFT0ZMAY2UcCsk3ApiH0EzNh+itQjxBHvFKZCIFOIQdphl0IqTueOpP7IqdHrcpbthV2IQkavEG0+fT8r5uKr+VRFZAf4RcAN4B/hRVV2XWPf5q8AfAbrAT6jqF/ZRt6mCbQlXz83znhsr1OtORWOXPcjpv5JrmiKFpN891+L6hRYXVua4+2SbN++16Q6mZxORagi+USLANhHBoI9baxCGAd32BpExBBoQhQFSqxFFIf1uG9SwYVmEYUit3sBxHYyJ1y5EQZDMTMQ9XUViIUz+1+oN3vudH2Su0SAMAoLAp9/tsLWxDhiiIKTemMdx3Mx8SGMa/H6PMPSTCEwnjqsAQr/PrW9+hSgIWD57EQBjlEE44BNv/yt+48lnCE1UGKALcwAKUTci2Agw/cQZWhvGJqhRwsch4glWy86uKQcpDUf7YRl58sj7MShcmtM0CoQaZ1QIutwj9qIxhMCfVdUviEgL+B0R+VXgJ4BfU9WfEZGfAn4K+PPAHwZeTT7fB/zN5P+JhWtbvHplgVevLeE6aSTfHmLJJHn2I94lzXmMcg5IgVrN5uXLLZZbHl99a4O1jj/FUdRKZKAfgWcbTBQw6Hbw+11EIDJCEEZsPLpNz3NwanUWz1xg+dwljFHWnj6i3phj+ex5xLLxanXUq2GikDAMY3UfBbGwkuaybItarQYiuLUaXr3OfGuB5bPnMSY2D6J0FyjIAqAC3wdjEoGLCH0fr24z6G3z1hu/Q+j7XL35fhALo0oYhfzbu7/Brz78dQITVrufFExgCDdCwk6YzILEsw7qZUniY6ESPgxxXMGqW3E98tq+Vsy4FXljb6gyaa2K47tg1+lKVX2Qjviq2ga+AVwGPgL8XJLs54CPJt8/Avy8xvgMsCQiFyer1vEjbce6Z/OdN8/w+o2VjBQqRD2HpHPEc165B1JwMWeHhkfz34TlhTrf8+4zXD83j20Vn+pRzdjuZWpYge1AUSOYIMAf9IiCHjYRdUeJVAn9Pn5/m35nKyFUod/tEPp9OlubbG1uDmMVrHiHpkZjjlq9QRimsQJxC9VqtWEUYi4AyrJtHNfD9WpYth0HRPW79Dpb+P1eRjKxaaH4gz7tzTXe+NJvoka5evMD1BvzkKza/Oz9z/HP7/wrBsYf3mjupmOzIcB/OCDcCpPwzuS0E2sLZd+A6RvCByEaauH4MNtSv8r3Dx2myfuv0n6WdjdG+mf+5N4xkY9BRG4A3wV8Fjivqg+SUw+JTQ2ISeNO7rK7ybEHnCAo4NgW772xzNULLSxrqJJpldmQoWpoGSNgOVVgmK9mv+s1h+94ZZlmw+GNO1uEkZYvO1Ts1VfTjyA0iuX3Mf6AKIqnAG1R6jZEqjh2g+bZi6jlEgx6iGUTRbHzcTAKOgoAACAASURBVLu9RXNhEcuyslHUsi0sI6w9eUxrMd4e3rJtPG84FKtQcCZGYUAQDDIiiJMNn5YCmDgeYvPZPZ7ce5N6a5nLL78P16vFC7XU8OXHv8s/vvXP6UTdbHZJ0xFdlahvCDcCot4wgpI0nQC1nClZ6iraiQgfgXvJiyMgpexwLHgzR8/ntYhC/hXehJxtMmmX2TMxiEgT+MfAf62qW/nRRFVVZLLQKhH5GPAxgHq9vkvqo4eI8NLFJtcuLCRTTLFdkF9uWxRrhkdkeHZIJsWr8sdzRzOCj1MLtg0vX24RGeWbd9tEU+iVjAz0InDtKCEEUBWMgiWKZ4FEPbbX7lKvvYwxrSRMOb6+3+/h+wNqucVQVhKAFIUhTx7e5+y5C5w5dw41Jg5/DgKCoE8wGBD6A4LQj8lADcZEePU5ao35uIxkhgOFwB/w7OEtnj26hdguy3OLw7BrVX7v2bf4hbd+ia0wfqPVcBSOzYFgMyBqh8SLQkefhdYUtSjKad4doRBtGKQW4px1RicW8t+rjjEi/sUysmvydkrVYLUz9kQMIuISk8LfV9V/khx+JCIXVfVBYio8To7fA67mLr+SHCtAVT8OfBxgcXFxqnq7AOeX6rx+fQXbtobCOyr3jNMG8l7rKrejZH+1eFSG+/ylxy1LuHmlRRgZvn1/+3BjHvYBJSaGliq2JRhNNisRMAiqghrF+AH9Xhd3zsdykghJIIoietvb1Gt1bDuJcUCyZdRRFPHg7js06h7t0Cf0fVSjLFKxqFoLikUw6OM4HrbjJmSrdNsbPLrzLTqbT7Ecj7nmEu2tTbq9Lksr53gmXf7hW7/I02CNdOowVd2jbkS4HmL8kpaQbweLZPu1UuPkIYBRoschVk2wFuwKrYGCoKc9pDyLMUxYzSA5heHgfQzJLMP/DXxDVX82d+qXgR9Pvv848M9yx/+kxPgwsJkzOU4E6p7Ne19eoe45pTYV0p02dxXNygS70X75uiFDWJbFa1cXuHau8Vw+hsMKKe+FmkRzgkgcPShqEDQ2vy2XRusMbmMBFTvxw2gcaBT4bK0/BRTLsrLQaSwLr9ZgrrmI2C7tToeF5TOZH0EsJ4lmtLEsGyR+H5slFoIw6HUxxhBFIWsP73D7W1+mvfksdnQ2FjFGCKKIXrfHV29/mZ/7vb/P/cGjIaGrogPFf+wTPPYxg2Rn6sqGBfViMhx3vmARhErwIMD0RmOVyzMeledLWkghveZO5FWeCbAXjeEHgT8B/K6IfCk59j8APwP8goj8JHAL+NHk3CeIpyrfJJ6u/FMT1+pYoVxa8VhsxuZN/jkPZ4rKvoEK7KS9lY+XGD1vVqQdShRcx+a1qwustwM2u8FkZaZ5VwZWyHM7LgIDG75wtgEWii2K0RDReDu3RqOJV59DRIj8Pr7fZ9DvEPa3CQddxLZZPrvK4soqtm3juS6OgZXVVbxajUa9zp1bb+O4NVbOXWBz7RlB4KNJ5KSa1JcQ77JsFEwwINjos7n2iK21x0RRCAhOrYVYHqFRjEasR21+ffDbPDbPhu0UKVE7ItwM0Uh3bZ9YW8gfYLzmkDxTHSjh/QD3mgderGWmz1ClOFVZ9jMUlYThgfJAVtAaJsCuxKCqv8n48e2HK9Ir8Gcmq8b0oCYB1y8uILmZgPzsYrmRi+1d4WsYF+GUv7jMPqlhnHPbpGQxV3d4/WqLL765QRCVRpv9yvbzkELinZNkD4OurzQcxbYl66qiIf3OUwbddex1jyhMFzXlzDLL5v7td3DcOo7rJJu/GjzXBY23jG+2FtjcWOfCpctYlsPm+jMCvw+RhUpEFMULkHx/QG97i157nUG/HQc1qRIZxfLmiKROFMVmyLbp8pv+F7ivT7PBNepFhBshZmBygsd4KSDVFkqOo7HtNYTpGsKHAe5lryCNI2HXaQyDUqHnD52VeZJIK7IPS+J0Rj7uGybg3IrN4kKTwh59ebJWhiHXO4zQw/5UHfEw4sTcSTZz/gxFObdS58pqnXcedY8/xiGpvGtB3YYwDOlHhnrNxUpJThUR4r0RgoDY80Ds0NXYbNDIMOi2URPR7w7obsU7RcfWmxD2O7i2w9bWJv1ej8bcPMv2Khtrz+htd/B9n952vGjL93v4vTZh0E9WVBoiVXDq1Nw5DBAGhgEDPh1+idv6MK5mGEcuRu0QNSQj+y4NLKC2xtuyZe2xS3uVNIloM4qdkeed4tqIgsAXB6aiRlH2LYxGVU6KGTGkUIMbtrl28ZV4g9DC3EDuoWeO3pQ6qntCMpBWqO65OYqcQqG58gppsxV8wyrYlsXLl5o8Wh8cf3SkxNpCw45pK4pCBmowUYTrWLhu3ryWESJLSdEQz2Z0Np5m4cu24yIi2LZFPxzQWjzD2XPnk9fYxZGSzYVF3n7zG4S+jxBHMQ56HaIwwBAvXOv7IV6jCU6DSC3CSOlHA75gvsrbeg+jhqgTEW2FGH+MOlghZGl3UK98hFGCqBLSNHkE0ZMQqQnOsjOadqdr05+p9pWcy4gjy2OyEWRGDAmsoE3djlhabAJQ4ScuOP2GE0Gxyl81cleP5kPHUf685GyVcVpATnFgru5yYaXO2w+6Y8lpYuzH16DxdGTDsbI9DzrbPWzbxvUa1IyFZxlcS7FTFVhTH9kwckNRHt96g7C/xdziKo3mAo7j4NgOlhVPYTbmm9kGrqkg1BsNLl65zqN7d4jCAMfzCMMaYejHBBAY3LklFs5coNPpEIYhvWjAG9a3eFPfifcz2AyTmASGFUxNOc0dytopd9hW1NGdTYcqn1J6Ls0vUsIHAZY7DJvOtIaMgXLSX/ZfSHkJVl6bmPyxzogBkLAHQYfWwgKe5+6kA5Q0gFTCy08/UZQr5KzyAWX9L9cR8wQyLH3YZwWurDa4+6SHH0741Mdhh96z04rVuh1rVWEUEoSGfmBYmlvA8xxQZRBGBCbAFk12cE4JNW6gNF+DzcaTR3Q2n+HW5rj88ntwFhbpb/eYay2CWNnqUzUGsW1ELC5duYFYDv3tDsZEbKw9JjTgaxd3vsnC4iq1uRa9vs+t+7f5du0Wd+oP8Ts+YTuKnYsjN6xVjzTnDIwfu9YUrPSEFNOmsEq/s/amIODqK8H9APf6MGx6LFKtoMwQhbUVxcFsEsyIIQoQfxNLDQsLzXi6LHc67/5LzYPC0F1Klf+tOnIBqWmiud8jnZDR68pTWEK8MvPsosf9ZwfzxqSdUE0KcR1Do1jEAU3t7gDbcZIt1+KdkozaBMbHj8I4qlHiRWm2ZWNbVuKvsfAsGz+Ikvcw9Nh69gjXqzG/uEJtrjWsgwiRMVhOPO1pOw6LS8tx5KM/oNZo0ogAr0Vjvkmz2ULFQtw271j3eId7+E+C2Lk49oZLt1l1yiHe4Xlsgtz3sm9hDEzXED4IcK96iJvbACbzM+y8sOp5/Ap5vJDEMHT4GaxgCzEhtiUsLrYKm3nkPdKpRyEdKRj20dJAW1bdigIl5QwKWkKZDPLPeVQntSzh0pkGD9cHx7SPQ1ymr3HYs21bhAo1ESwNsdRCxMK2HHxjE4UBkOySpGBZIa5jUXMdLNsG20ZcD6tWQx2H+sIZWivnsZNVkCYTkmQ/BeNkOxnNzc/T3U5ed9+0sLw55qIIx4k1wPZWmzu9e9yO7jPY8lGjmbYdP+vUHKiwF8tuByUOZ3bN8OBuAlnlN9CKazV1Rga4F92YRauuL1wy1ByyLpufwtyH5jA1xHCUm6tmJl7QQcI+FvFuwPXacCJain9Ix2wpZDA6kqbxcuk0XHnzNtV8BkNSSBcXlSs5TgNN/y7MO7i2MDjGUOlI448lFjXPIwh8jCoW8VueFLAcDz8YEARRtk+jAAwU1wm5cOks56+/QnNhiYWlFeqNObxaHdBk70erILyRiTBqsJNgKct2mJtv0dnuEkRxsJUfhGxstllfX+POozt8rvc52n6nICRDTs5LavkkIyYEjsbvlcydq2SIceeqtIrUGlGInkZIzcI54wwFP+1TUvY95MtKUpf9DifVx3DUezlK1I+JId3vu6L8qoGgysUwDpXKd0nDGJ9FhXlSkbjuOczXbQbBhLt9HiCMgm9g3hE816HXHzAIDSomjkK0BMTGqjUR+sn0YpDt0uzYhtdXL3Pm3KV4FsJ18Wo1gCx4L/NbJsQqgIlMtqZCiB2Rb771Dl/80hdZW1+jvdWm3WnjD3yCVkBwI4jV/yrLb8cRmcR8S9KJYryKh5hKYJafFL9XQaoLz5yRXhw2Xa5nWQsoOiqLCeO9LCaTr6khhqOEmBAGm0iydW5uX81CH8mrmYX1KGnCYqrkeKJZjOtoWl5Dme9VRTMif032nEsP2LbibebWO+GRk2segQFVwXUcLMejM4ioq+DYFo7tYAA/NETYePV5AtOl3+8TRCGt+RathSUgIQKjWbsPw5PTdRFDiYiiEMeJfRmKYDs2rdY8n/+dzxMEcWRovN5CiGoGIuIenw2+SnGpYgVyzztL6gB2SgAlh6Pkv2eOAUanC2WYabmstMhA8e/51LwaEs8Hj0vKaEBUno/2YusUceK2j39uqIK/hWUCJFVnR5Y/59OTmAwMNc18B8g1eupslEKW1ZpIeoGUj2qF9lSoVEkdFViYczlu+Cb2AczVXFaX5qnXPAah4oeKYhANEZMsjQ5DbNvFsj0iY7G4uEC90SDdIj59SUwUxduwGRNhwjDbiIWEJOI3TQ33ZECVmzdvsrS4WGhDFUXryctgtCQiUjIfCucK/5K8iLUFyZ9I7UEZsUZG7QQZqiClw1XQnuLf9TGB2cmuLGQ5WunRAWU3vHAag4TdeHpS03ct59br67D5sobOaLfUsKWHv6uFUW0J7H5dRVnlY54jVTU8UkQKnSBizlY828ZpuER1GwuNN0aJYoLo9Pps9/qxueH7eF6NM8sr2dbw2UCa7LaUPhuj8d4Nw9Wuw3dNxBu9xnffajZZXV3l8ZMnw8q58UeiihmhnVqt4pS6WnrpbPo8SqPyiA1azjA/2shYYgAwbUPwIMC74iG2kPkZ8tGNo7bFUMOZ0PEILxoxqIFgu8LIBIzS7/YLzymbPCireKOHhgfzI1WmkewmtOMT5N89UR6g0i+2vY8nf8BUokDXOPSNwZMIB8UifnVce7vHs80OTzc3aXf7+P7w9XPXzq+yOB87GdOpuMI6lcyGMvFO0rYdv3w2aWtjosJ7JV3X5eYrN/n6N74xzKOerGNQYnPCIvecpELNL7Z3ogjGzjxXiw+iIIB59TKHbDo6b7bkBDnrJKVhPuenMM9CwpqFc84Zts9Iv8xvMV/ObzK8UMQgUR8xPlbBhEgFRNnabKPEc/JFa79kR46DFhOVx/Ghz4K4k43PpKBpls6MwLas0h4Roxid9TkYUoiiiCiKCIKAwWBAv9+n1+3S7/cIBgMGgU8YRISlVyGl8+9nFpvxrkz57e6yrduSPwlLmzAE1ys0ZBRF2PZwy3kR4cb169i2TZRs52YauWnFiOH7IrMRexQjriSIZyEy30JyTIbpMp9fpbaQfKkaxstVqBjm1UD4KEC8JGyahAgKq/tGscOpHfHCEIOgSF5byPsVkq/trQ4mjBDHKbzdJ7egIckrO1FRUo5SKt3fieGR2SxlozercIXVoMVOlsCydnB2jq3L86PX6/H222/T6/XizVtNPKqnr33bsR7JWpP5eg3bdoZEnezFMHz/gmSDXxhF1HI2u8JwR2nIpPTq1Ss06nXanQ7iCOQ3CItk2OYVbZYfKjIIYCXaQuFehueHXKXp7Y1HpbRKkY2q6hYowX0fqQn2fMV77nJKgpQykgm1yhPnfNzvRiNqojjKEYhnDoaOoHTc6Hb7DAaD3AbOu6oHpa+VesZIMpHc3HKRgUYSF04lD16HPwHwA3Ms76GIooh2u02/38+IARhutJIgTxLpOSHe17Fe8xDHKmjVxWecMWj29qjYz6jJMc3KTR/m2bNnWVpOZjncZC1Dqr1nPDLCugWMPDuHJPS5eHlenrP/OQEfyb5gbpTOKrv0OdCBEtzxk52kRgk/b6kkCQDwWh6T4GQRw3MEQYnx4x2FEvNhOMuQdhohDCLaW9vDabESyo8gvXT4NApnS70rL/RavE5KV1cRRWqeVNx+bxDt3J8OcVvpkY6ZKyv9Pi54zbEsap6LY7t51sSSvCkRa1iq8UatJmeSaFK+MWbYUgKNRoNLFy/FaeqabbqqEEc8RhTyp+JnUWPQOMox5z7Inl9K2OVrKsaNfB3zrw8ofmSUlUqZmW1DcM/Pdpsu8FxFkIzlWTjzk81cnSxieB51OApigUxlPif8mqqlkeHx/UeFzpcVTdmE0EL8Q3V9q29hpAOVOaR8+Ug+w56oqrsvvT7E+IYqDa6sMaTHyuTg2DY118V27NwAXGxUSY8liNJXy6HZjs8mimJzI2kWx3G4cf167KRr5G8/TiDlHdoqmkdypoZ6CvaQDMpO4GLfKB5Hi2Re6HvjzIlMc6iqWNIO6xHhoyCegh1Jl9PQLMFteROPDSeLGPYNhdAfdswkVj/eODQxJwxoBE+frNNpb4/kMKJaZoJZJbeaO57TPgo66JivVWxQ2MmpWKCqJhrD4Qn/ThhXbpUpkZJD+vEcOw6IslNXV0q4kjkSESvbOVpEEnMiSmIY4lfPhWGQxDxEaEIc169dx3atePVj2Wwo82jJyV+Qy3RZNUO3RPmO89Zg+XzZj1j4XUn4ccHDEksXpNcYJXgcEK7H5KBa7hfxf7tu49TticeGF4MYcgKZknWm3g2fBUZh0A95cPfRjoJW8kWOjMgjV1b1ptyIoHl9NFacc1rmsLIjLxtB8QPD5nbF/o/HDNXcVvsV5gVAo+bFu0Lbdvz2KX+AP+jFezmmjkjiW44Cn/b6E/rdDiYMY5OA9AUy8Vux86Rz/vwqtYU6OMMp4ww5jaHKZxNXNP6oq9kyjaoxvOLlUYX/6Y8RLZHCo8wVms+3Qq2RXNoIgnsBUWf4Do1ht1LEFtymm3SjyZjhxSCGpJFTNS4NZNJUUzDx28tUBWPg8f0n9LrJUub8LMaIelfRVQrRjMXT2QRlIdahdPmYX+XJzfTXetun5x/fOolxiKcjq8+l5NCo1+Jl11FIFAyIwpBg0KO3tc69N7/G2sM79La32N58xv23v8E7b3yVbrLnQhjFWoKmr7LPXmkfP6elxSWWLy3F/gUozkKY5FNZvxxJ52YipDzK57tF7nelw1mKv/PaxVjkBLzyeMKY6sfOSO0nB3OZOnMOlmuPdrI94MUgBogb0cTvHcgch6pJSG2sLURGiVTodAbcv3Uvc2plREJepitEujAS5DSC8ohRcXW1RlGdJtv5SJVHa8e15DrGuFmi1M+QDz7K35KI4Dk2Tvx2mniz1jAg9AfU5lpsdwMeP3jIo7u3eHj7LR4/eMj2dhd/MEhMiOHbp+Lw6aJ90GjMcfb82dKonBPLvAOyIOwJgyTBTDqcvBrWPftT8jtXPOf86SrSUCUXhzTuOeY71uh30zX4dwdoOAybtpzY4RhrEVrdn3bAqSKGsQyctEs6t5s+EGPidx5EGv83CiZSgoHhnW/dZ+3xWnVmOYHPjmqq3KcFQrFXlvXHPIGkv/PXSfnKQmoF+oOIZ21/PwPCgWAnUkh9AkWki6KK2le6UWzo9zEmXjE5v7RCJDaDEHwjGMvBYBGGQSF2QTXZZ7LfI/AHiYkBRiMC/FLxObUhzPcJhqNw0uJqgclNc+alu+p5pOfyBwp567CIEctyrNxK4VpERvpMejLajAgeBKTz1k7TjZ2vWXNP1ktOSYBT3NRjb10ELBdlQLo0NZ7/hqxzahxOGhmDqNDZDnjjd7/NB1tz1OcaI1mWO5UwbpAf1RWGfKFj0uX2fsiVkX1JHvTtx116/jFvBqvD2lbOrFRNZ2rqG9BEa4tQP8pIwRjD6oVLDELDQqtF4Pv0fUOt0cRxbLpb69TnWziuhyQ7bkVhSC9s47geXr3B2uY695+V33OUSVimMeQ4mLzAqafFYTN/c7mHUxByLZ6v0gqropSF3PECe+Q6WXJ86HUp5a4QPgmwakLtah27bhcdkhPOSkwtMUy2cUsxnSUWtji44lB36jScOebmr1PDzjpiZOKOGEYB3cEWW9vP6PY6hNEAS2PSePZkm7feuMXr7381nlLL+Q+G+3rkRLrEDuXt2Eo6a3W6fFYU88uf3GwH3H7cG699HhVkHCUUkZ8RSsORo4QYwkEP14v3Xwj9Hg/f/hrXXv9O3vu+78CyHZ4+fcrA95mvOTgCgd8j8PvUGnPU5lo4jgsam32+PyAMAt689U02epsVgpHOQcbTllolAQ7ZTMTwBsbcV0V77NwQFFwBOjxUvD7XVYo7wWvxgmSQkAh0AP6bAywVzGYS22I02dPylGgMeyGFPFuLCDWrxnJtmdXGORa8Fp5dw7FsLLGzaLtSmyZlGYIwoDfYZmt7jY32E55t3GO7+4y3vvWQ5sI8V16+FNvL+QdW8ZCG/3L7Lmj+aOk+KfNJPpMKAtF4S/S3HnSOdXOWvSLmTi38jgdEiRdAERF0N3HcVVQN/vYa3UGHb7afsXr1Vbx6/GLaeXtAuL1Gd+Dh1edxvBqD7nb8jkqvRq1Wx/FqiFhEUcg3bn2dMAqzxtWCqZD8i4jXPuSFWcC4OvEIm15b2cHGzXPm20mrZzgKl6rGdTZAqHGAU0Qs+OlMi1G6G9s4lx3w8o6QyTC1xLA3CDXbY9Fd5FzjHCuNFRrOXPyik6Q1ChHHCYqDiCCWTc2zqbk1lporXD1/kyAY8GTtPnce/h5f/+J9ogiu34zJoTBtmHa2giUQdyzNpRnhuRwRVOsYJVJIg7FUufukx+ONkv38PNjPtvE7IF0glWlY6T6aWUBZfCgyBgtD0N/Gm1sgCrqEg+34bVLb69x947OIgOM1aLRWEctCdZt+ZwPbdbAdj2DQpd9+hiUwv3SehdWr2PUmbz96h3S41byw5jFihclwO/idsFdBS+Uybd78KJ8jkZzymZ2PZ04UEwJhSggJEWTjQb6eSeYG6CrR0wj7vLNvL+KJJQbXcjnfOM+15jWaXjPRCvIp4lbfvbsrZTkXwHVrXDr/EhfOXqPdWefxw7e5az3j8ksrWLY1HOZL1kLqsS7anpolp0r0x5JG6bAqD571+L27HcKDnInYEynsPOSl95aPehSRbEFVwRGZmF9RlLz0Ngrpbz0B44MarDQ0MVGTo6CP329joUTBABMFGA3j35FBrJiEOltr3P7213kahNx+dicuCqVyBIdklM3dV36hVJVtnjfvq3wFWnqmqdWio8eyfCKNp8wzAtA4YCmdUs0yEIavQS8XLsP+mE5MbBhMPcJatsfWdyecOGKwxGLZW+FG6wYr9ZXkrVGJ81GHWkKMpEWShq1y/GguWfY798WybBYXzrLQWqG9/Yy1+49YvmCwXauUT46ICnyRm6kYSZ+m3ZkZ0imnx+t9vn67jR8ehwlRQQoFTWA0DHqYrNpftNbe5ulmh4tnWhB0gHgPhxRWIohqQoLtZ/GjNPHUJihBZNjuB6xtdrn3dIunm12ebHYZLCus2rmNIhkKRl4w01E4kYLCy2OqOLAsYKXfY2kzIQBMovbntIBscqbQEcdI8kgBpTTZFGwsC+apQeoW0pjcljgxxCAI8848N5o3OD93HtfOLwopNqTm2neoM+SlVYpe413sPwARi4XmKmGwyNb9hzTOtqk1pKilFDp/KcOCZlHUNKq0iSylxvEVj9Z6vHGnwyDUwkYmmfPzABWIPWPkfqs74Dh/0Xbf59Nfe4vve9cV6m6y6lI0NgUFLJFsPUr6P1LDZqfPk/Vt7j1r83ijx/YgIExeGiO24M65GamMVK80aouRTKvQWsWtVJFB5U2SaZAaEQtpWQPQ3PWFaa1yRlIqt5ywQp0xxT6FKBqAeRJiXXLi5ecT4EQQgyCcqZ3h9cV30fTmi16arI1KjZUOyKkWVshRY3Vs1xe9DHtSbC8LjuVhmyv0H2zSqd9i8ZyF49oj3FKoTUmAihuMVU+zpvX2jeGdtT4PeyHu1SZzTQexBTWxGh0FIf62T7AVEHVN3BnTON9DRllDqFoTsRsernf4xG9/k2zKXZMlbYngpD4KWyRL0xuE+KFJNAeK5otnIbWyYDFWuDUEPEEdky2rHntdilQI846/iNgZWBD+0nX5zWHzyEgrveGUNKoqXcFukOxnqUMGTavaUXgWYa1W7N+wA6aeGCyxuFi/yKuLr1JzEkpPR8m0M8BYghi+34FRH0S+g6R9IrPjKAhvojQnR4SavUS4Bd968GXOX3NYXGnF244hhbxH4hMKw7vm/hV7S2RBx7V4Ytv0FzyWLMlW/KnGOyQHfoAOIsRV1Avx2z38to90LWo6hyOTbhK7B9Upfzc7CP4k081BNNxbIA7SG270UvbWqw6FIh9VmZbpzCejY+osqlRkhplKGD8jdUrxJanvwcTmCyEZEUiy4K743MoDSq6c7HFLqbPm0o70gXzlC+pm7n6S/FOiKtzn8HqzYbAak3khp5oYbLG5Pn+dl1o3cCy3evRXTdo7NhqGvJCO9FnCzAcBOUKuUhqofCQj6eYbi5w1H+B3f/uTOI23uXrjHKsXzlCr1yrWCYxb7TD8rkBgwWbNZsux6CWzo8VXH8ZLjaMgYtAf0N/u0tveZtDtM9ju43d7BH6AZSwadot5ewHHqrGXWINJ1YxxPoV9r/TM3n8w3MWpXMSwTBk57jgO0sxpY1nsRPI6n9xuMNkOUckAoAD+cAowNgF01ARIvxbU/ArVflhQ8Xj5sQtDzbXSf1Fqyyxtqn1obul1jkzy+UUQPZosEG5qicERl5utV7jSvIIt9nCsLu+MC4lloENySI5lKlmmMSSdLnc6RZ6EUzHNE0lZqNN+1Zpb5D03/gCf/8a/5rP3vs7KSoMLl86yfHaRZmuOWr2G47q5Z0XdpAAAIABJREFUDj0kATWGMIro9wdsBwHRUpPufIOBVQx91VK5sRkREQYB/e0unbUtBt0e4SDAhPGy40gNnXCdXrTFnL1My1nCksnUyf1CJBHOCfkh69YTbh6QhmDbro2p514glDpHy9KYkyENlWgrRPvD0+Mrl79QcspA0Xyt1FDG2SeFuHooTB0X8ssdrwp4SDWc/FZYWb0UDSZ7GFNDDHm7W7C4Nn+VK/NXsLCGI9DwPitNsOHU1IhHoTBTUdQAJdE6qli9qDeUSTzNpzm3yAde/Xf41Fd/iXuP13n8bAvHgZrnMN+sMddsMNdskNoChjjqb31zm/trbXShzrXveTcri41EqAqVGFar0IfiFYWBHzDo9gi6/WSRWPHGQw1pm6f4UY9F9yyeXZ/UYpgYz7M3RPbu0PIUZ0UZKSFYlhW/RNdNFj7lNYaSOZHWzETxQqxsylmIt4UfV2QmtGSJCreZV2TGEkS+BmNvbPTCfIdNCSolEFO+pqLwyXgW2AMxiEgd+CRQS9L/oqr+tIi8BPxD4AzwO8CfUFVfRGrAzwMfBJ4Bf0xV39mtnCEpCOfq57g+f324xVd8opAubisZVdl1mKZo340ruKR2jqtZjozL2gMIS60zvHbtw3z6jX+JhgFOKFiDgMedLiLrhCiRMQShoTsI6fYDtO5y/YM3ed8PfAdz83O5vLVc+qhGKfE267ZjY1s2vpau1WF/UlF6UYfADFjyVplzFsbc6wTYQ2dLnYL7IYqdrhMRbNvOFmplZOIpag37UboKFZJBVTXZ6EVJta9MkH2NIwWdJHUxDnmYSfqlcneW9Lq08XNOoUrTY08tUUxfHp1SU0dK/URySk6azQTYi0diAPxBVf0A8J3Aj4jIh4G/DPwVVb0JrAM/maT/SWA9Of5XknR7RtNpcrP5Cq5V4iyloj13UVdVs5Ypa2xlbU1zn3xZWvpemHfO5SECL114nWtn300vCGn3fTb7Aesdn6dbA56t97n/pMvdJ9s8aftYZ5q89kPv5f2//wMZKZRtynQRTNFPkoyUto1tOziei9vwsJzkBbKaa5aiwkOoAev+Y7phe4dG2yMm6Nv73cA3l0OmHTiOk30KKzgFtA6SxZ4N2y4lhSiMiEKTnSvAgAQ6DC0uyGPFzZa02OGPXN6FcnYboarKy6sheY02IaU0nKXQvikZjdFo9ohdiUFjdJKfyTt9UOAPAr+YHP854KPJ948kv0nO/7DssWfUrBqvtV5jzpnLHmY8ZpakMF8/dPxgP7wJUqFSTclVi4KXfETTEstquZInmnxlJEnr2A7f9coPMO+dZas7YKPdZ3N7wNpWn6ftPlv9EPUczr6yyqvf/zqvf+B16vU62V3m8h51VeZ+i2DbFrbr4Lgubs3Ddpxc2jRd7pKknpGGrA8e0jsIctgDqvZ/3CuGZkJsKqRkUJ6NiBMTv1iGPOnHGkIURJggir33BUUgxxwQzzQMVa/8XRRHk7weMjJgVakZUpFnOb1kpubwuopRqLLcinplWrPuy3Tc0xyGiNgi8iXgMfCrwLeBDVUNkyR3gcvJ98vAHYDk/CaxuVHO82Mi8nkR+bzv+4gIVxpXWPaWhvfGUGg13xZ5YU4SxzKrxevStIWSczZovqDkfzlt+aFo4XiJKxQW5hd579UPMfCVdj9gq+/TiyIiS5hbmePCuy9w7Tuuc/M9r1BvNAq5ZmXk7yN/E7lkllg4jo3jOTieh+3YowKY5ZMSY/w10pB1/xH9sMthI79hS7Z1/B42d0n9BvlPmqYSNqirQ43aGDQ0RGEUT38mTz2vcVfO1BgggMJ+/FVMWx7FRxOX767YibOP5v6XB57S9eVi8kRVQRKS+zsp9uR8VNUI+E4RWQL+KfCuiUsazfPjwMcBFhcXdU7muFi/QBp4EPfn0cjC1DmXn0UAQNLVjMlrzvLnyipVLoNcacOEI1pJue5V9wOp2/DmxVdpza3Q2XyA2LG3fH55npXrZ2idaXHp+iUayR4PuxO5lsgtHQlIhMfBdm0s18naLn/BqI8i/hKagE3/Ca59GdtyJh5RJkGVryHvXEwfx7i9IXc6luWX+BfU5P0IQLqqNjUp89eMyU6iJJ1XugBl1PdQHq1LpyT/ZY9Dd6G/5q5Js1ES4sppCCPmxNBrV/Rx7A0TRT2o6gbwb4DvB5ZEJCWWK8C95Ps94CpAcn6R2Am5Q8ZwybtIzann+nTO05cn73Gsmjs8dFAOzZDsW3EQHfUZlAaKfFElF0C+UrlSodlo8b5rH+D/b+9bYy3JrrO+VefcV08/ph8z4/aMxzPjDIpNEmwTOY4SIRMUBMZK+OEQQwQWimQJ/gRFKNhCQiCFH+EHJAiUYMlITkRwbCCyZUEcYycIicSJHcfvTDzjmfFMT8/0TL+77+OcU7X4Ufux9tpr16k699x7T0t3tW6fqv1c+7G+tfaqXbtG4zHWNtZw+qHTOP/YBWzet4lzD5zF2fP3yxqSBsQJ7DjumkfOAVlVFUbjcbpVWrIqsUG0c6/ZwZ3J9Q4ttVySFoO0IEbOQuiyKOTbpXnBQLPRWgf1tEZTN3IyKOAXs6vwBIAZrdVQcxqhH21kml8AQMammlylx5cZ+XawAAVRp06nNZ+/HjjEc4GBiB5wlgKIaAvAjwP4FlqAeK9L9n4An3TXn3L3cPGf5zlu6QoVHjrxkDLtxKGqBtCmW261NHsA0TXFwQl+BF+WhBA52H6mhPrEACtACOwS4fsf/X6cPXMepx86gzMXz2G8vo6t+zbx+jdebN/O9KUEE7LAruJdN4uIACFYWYLCtfdp3JpcX3hJsYjvIDoLu5cVFhWnEQM8Y3fmYaJFUOpYoU8NJt3vBAIcjKcUlrR1LQdYFl4aJCOPxi+JAclFNhMBbz0PHKo+S4mLAD5KRCO0QPJxZv40EX0TwMeI6BcBfBnAR1z6jwD4DSJ6GsA1AO+bV8EarWFjvIn28VJENyb1tWjOJ2PYny/MqVBOSKRrFOibqdNYgs6S3spXqfP4c6fO4c1vegtepBdbP8B4hIfe8BC2/BMIT4kj22vFtJ6MON2LQYAN8SorZaUxGp7h5t5VbIy2QHTwR4DG8Yr3fcBBLkXkOxmeRjsjzE605ynYmgSmcCRWmY9vxO8E7YP6ipGcv2a9+myOlShXLivMR5iFMqTcyw/MRKEIiXJ7wX4XZx7NBQZm/iqAtxnh3wHwDiN8F8BPDWEivCkZ+rttWvI42P34l5l0DwTt6/kIwk/xK8QJo2V+2uSirJICUBpdPsEaVSM8fO5hXL55GTxljDcrnH/wnHoKlsCBodwsHqK1IoecoL8XabdLFQsGsDvbxl69i83xiTxTB2XHtQ2kcKAL5is0aS2Y/ocpoZpUqDdrpJ9+QipY1jzoULhgAFNu/Q1eE5hryjkTKimXUwwI/HZZGuI6NRlj/4dxEL4aJrD1XcM5tBKnROtDPFLtjdAZyWOoPg4VRiJA8sWcYmcz4ufOWAF74E/y6JlzbRFJL6ydB+8BzazGmQtnsLG5Hi1SDQoF9uOFZloQUSKYnFz5x7Q55ERLu8GdyY3BukXuIRhKifY3+Ouq00zLwGh3FK47LfV58UDaphqtz0H4LfZFXfNvbpoEFdr/ySk/UFlGBvK8EsAAoADARo+JoPC1o+RZZqF4jt9iCAZWkI7Ykd7TEP3l3mwXyORzJGAl2HP/nV47hc3RJkbjES5cPA9yz9/9dypCjmy+Sf7s5gdlQwi7IOHKT9aUxuTSwAEAO7M7mNWTUOYwshbAB0OpCyGti3ZHoJk62rmLHY7JOtMw3OEqRl5W6fZD2eCq+AaqjgiqYa+PfLvYb69fgK/VAQag0LneoaZWS0KdRlEXHaXBgvOipfMxARwdpjVUNjj+0l+35W6Ot3D/2hmcOH0Cp86eyhymcn0rHZtyMKNb1Bcd0ch/27EatU8lxuv+yURMI7opZ120tW5m2J3dDc0YQlL7L/SAQ7wfMbTOpJiaMNqr7HHTgizDSxpb309hgEPr4BNc2PkXMquQ8h3aQ+IP0Z9GOrPJSC9aIWDIB7GVAbHv0ZrlbGY1+oij4Ko/lhl6In+ccx6V80wjGuEEtnDq/vswXpM7EzUQpTo8gosGJK3+gWpUYbzWPhZd29zASNaj+8tfK+un3fbP2K13FlZ6vZZ25cyOD7kcKnFS5pAAVDuj6DzUWSztLgWOVaSuKmx+0oVzZMBUXrqOAeR9EQkoxHrjOyHGcpw5ph84NisEDH4ydPdcUSsZwp7tYUA6HzyFE4MkIokyvaYPB4lYFapWhKA9xolTW27S58KegEKOgIGPTEMyQFWFkdvDsLaxjvWtDYw31gHj6UKxbwVGTGa7aHjxD9hoB+hQShyMPWeyfixdTStUU9V+vdKRk8Cvu0IYoShFwRmJHHxk2Rq/h2Ncns46GZrj/InKRvDugaqjSSVaGWAISh2+kfIPWSfOdVoFoRZ5HYoGwAjCTqI6vbdBaQDlWGBRT1wNxDzj8RgnTp3wrRKNFSGpAi9BTdpXcBpyNGqXEWtrWNtcx9qJzdZqUMIQHq1KzFMabdZMgp9hEQr9CbFRSy8B+5YxZE0ive4NUO1W6Xp8vr6RHMQ5F/KqzA3aJcVQ7Q8IC6A/OxHAZKD1uNTHqbzzfC0GrQww6EG0wNdQpMHDz6lk5lZFJ4rbmrQrGnLuCIlPd9kBm1sb2LxvU7IWASfhg2N+KcDa4ekmLgNuByFhPB5hbWMN6xsbWD+xgbXNdbcngWPJnJaS1OsiG24w3QcwiAqC36D90E/cXzKXFtBuHtDb7ITR3sj4ZgRsgRRaty1IMBAAgtIJyRBPKgrlmoza9WfxMsx9XyKPY2MfhPc76Tq4H3+CVgcYpGDoGOl1NcBBKT43z7Xm4eQnKyQpwCg8y8eiMqXRwyAyNk5sYm1jLeRJHI6i1brsYDXpclUqonYp0b4z0VoO4401t7uyddySypOCEUU+mFHvYymhmZX9H/afzM3n2aLAU/8q2/po5pYTxrFsST2OqPTShHQkakXCCOdAZrxDpx9AnfttDKE3Kkv6mdA6pAeC7cqc4ATIPuV8sDyYg4XlmDpWSmMhwSHfm+LW/pwU5bmAf6V6/vNgzn4YQF3NsOE2cHGWXwm+CmIrnddwcmI7LeEPInGBIZ/lhIw+rcgwo33zctmU7Fmgnv4D5rA/Q3Z/F4U9Dg0w2huhWWvad56SzURAKDAbS+nAMyrV+Qit1QC0pz9Zefswr3nzFE5n8vE90EZaQL7qBUBqdSwGbaol1kMqbdHtIAOEhrW0hNbSQbba/1O5FxBlWQ8F/oNl43ip6xq3dtuXlFKrwLIGLOuDAw9lV4r7SO+sxmwyxXR3gtlkBq4bpDNSA5dqm/ttmgEWQ19HY6LABqguNa7zliLtTsr2utobgWYda+u0O/Ju979mx4ulRsPdzsghlA/9sLzsN737ZVyrChcxXlYDGLjQB4kKVT2lQCKGC3Rhlc24T57scFquyVSSjjO25PVkNsHN7ZtxQgeHpsqiQSIw1/6Qjk2Eu/2+xGw6xWR3D3vbO5js7KKpawFIHLtGdpPiF8Rgc4bb1FvEWVk1C0xV+6U4K50zNGoCTav2pGer3Z4vcZ1OBMTfBJmNicGI/gYZZl3rfJ1x2eC79CVHjOTRpfHtuVeXEsk7EIjjEPrG3LzhItycCQfsOpOMklM5tJ2mnvsKGzMbKwdQbax+FUmrnkjbe9u4vXszHDpqiX/XiKW1FASDgaau20Nh7+5g9/Y2ZntT0YGiieE3ahVddoV+J0kPfSyZgR/3e3nKLGfOcsRXNZqM0GzUYK/+KD6dISD5bGV4Yc87GkMCpOiRDJuYrDWAKbXnm3XJbK9GivQWwKTDhzjhVTHOguIs/XxaGWAA2gnq93yX13eqh7V8+7Tivs3G6fmdbnbENGnmtC89Qhe0hcEqGLi9ewtT3jMdaHrdP2RDT/KYE4ymYTR1u5RopjOg8cuIQpkBHPLuHOmzNktcpY85hk28MD5xgIYtMfrVV00q0IzAVQOMKOoHWURWjouR45PqDSQTR87VmtsPbs7rQj00lo7odLpytMJ8CMUebMEzIB6K86CDVmMpISiIpegYaeUx0r9gKnV0ZBB5kVErzqzc5F5vS1YJZXqOQPTy7Rcwm+5iNp2lvGa2Q15Q5+NWT0KT+a9Ky/V4aiWIgsTJSUnR3O7WHKpd9k1D5y3lFoiZjAnVbNR+n9INjrfekiUEgHDAqp5ovsIkfTtxOCnA9bM/UNZH6eHu44gUx8plgEnxT+/5sDb/SSUyhFYHGFQHtuPjJnqX980nRuyotBPK+RMhh/Er41M0ApBuwvETz4fvTnfx7PVvY7a3h507d6PAZqxwWq+U0kyrczLQERM5THqZnUVe2Tfx5bM2zgMZQAsd88a0iNdgHyTaNC9d2NPAjOwMBTk1fHwYH6FBtMBxrDskhQAWuflJuwMMhaLblQYZ2sfMa03exWklgCFBXjHhpcy0cRrJbVAOO+86HVZScoS0ZkKaIodfj2cCpyp65dZLuLH3GupZjbvXbxktNhoiLxM8U5OQ/YSJuwzbvyZMYpEtBRNVFwL/1B4wO1ovdVgH7d/EkG+c9t352MdHUc0qUEPiqQGJvpXzqQwacjx8ehJ/Pj6U0CCeNm01owsc9FerLerK75riLY2Sm3IerYiPIRrq6bqe4ZvFIaS0FyHLYlST9mb2vFfcp4DUESeZc9cNN3jm6p9hxlOsYYTbV2+gaZrs2HPtZzDLTpDKSCVxjbMmBiBLcpFPm5a5NtrEuBr6IVyESoOSXPR9CeWgneeg9G2L37k09jw0zgk55qgGpa/KXXPDiZoMfkeS38KMGBLFzvnFkg++cFxODOnOTkCwfAUyTDogI8/z4dWm1bAYGnWEWyAqTvrU36ClQ6RRyJ+sTLTMiXymKZIwLZigqIGYGbd3buO7N54FVW3Y9o1bzs8QG5E7H7tAQTTaD3loqtgmLTooAJ0uVOTT4VvjE8nXv/b/oZjYJ4OIkH5hqli4/2HAb24y6qomI1ADsaRweb1fQZSnfQ/eqvDWQcKQtEhl1b78Gulr2gX+470AK7k0MRPrMAVMEEUtQCsBDNN6EnFPdER8Bp9qyGw5lfWZNUpWOhElgKMfyRkR75kZ37ryNdytb2I0IozGhMmdbdy9cdNY2ZRRXQquCRoUNWb0H7CY92VEkya0lyWiClsbJ9OUQwXaoLnCbbMYl0eIlmJXejlwmu+qrsKehrSYqEj8TttMYcQkudKSJampyj6wZvu9DbMNsu599H3Al3v8oJbZbA+TSfu54aCIs5Fg48+IzgL9ZSl/qUwlOYnwaaGNM+fV26/gG69+CSAOJ67Vkylee/6lsF0580l08B0mGKuNUZzmjx5pz6+cY97ZyDpbaMHaaAMbo03NSH9KHhtz8rfIeZCisAhkfVlx1oPc7j2auHMa/CfoQvmhGnuKFaZJ+/0Kl68RKwk9dxu0TyqsfWNi+amtj2R5rHgdTAt0/0oAQ93UuHbjFfQXeBGp4zrwI9cGbKTnJDwZK51dXUxnU/zJS1/A9uxOfBTOQNMwblx+FTu374QSMgslESbZnii+sc1xOeGdjlLDhvQcy5flBsebS00gnN4423sPg0m+YmMSkmjfIrSfY+b9dTWtQLU0z9UyQpoFfQHCZ3PX+TLE3TfUOiP1S12yfgkcLCKt+nvSfiy+lQAGgPHSlacxmeyJSStjU0RPFW57E//Zsp4VqMtX19lYFCeHH0DCs689jWeuPYWmid838FbG5O4Orr5wOW2baFQ6R0XevKsiueVEI0AluKPChJWPJsUTFI9/DTCuNnBy80xe1yJksSwkZ5EN0elz+vy6T35qCFXt3rj0rzJ7fiVQlCZCF1ggnZ9J3f5/bzno8j0/Q8ioxyLah7WxEsDAzLh+82U8f+lb8SUeZb5rUzoR1mxQFLwma1URaw0iq4AMAPLyGYxrd6/iD1/4v+48A4qjQkDj+L/+4mXs3d02gS+5Ujs8pXM15T/yxI2wNkQ/RBwQ/gfxCwBnts4u9jRiKLF/jDYcHhKfC3NvK4Lg/BwMjKajtuF+n0EipIbQ9gEJYQVwKb23JWoAM1FPbJBsaPpbbJUuww66p52PDQOTeoZLrzyFK6+9kJjEXZQBBYDi7FfhCThYaJ8gTwyMVkkUytvbt/H5b/8uXr37SozluOehrYexc+sOXnrqGdR1XOjm7eRkjgLiHAOSA82h3FAfC8vJRD0IftrrjfEJnNo8m3HRhxZ+1yEIEmc9XM5olNMzW1xOjEC1m/INUhDtEn4DBIb8ecBmRgQHT9JyKbU56yTO482G+6jh47QSwMBg7DU1tqd7ePbFr+Lu9k0XbvRH6GEU+6c0ZZIVeJe3SZvbQQhjEt/VO5Nd/J+nP4dnrz2Nxn1MtW78+wvtNTetn6GuGVe/exlXX3gpgh+nXDMsX50QJquFqj+yYC+AKn48GuPCydcdjrVQoEU34MDtL8iwvIua1tfANQD/XZougUfHvY6z0llpGoT6s/KS9sHeuqCpC1DcNQkF1ZdWAhgAYFI32Ktr3Ny+gaef+xNMJjuJ4Du9GDME4eWk45PgPp2h8kotkvSvIXTTeoYvvPD/8NTVb6LmBg0Dde0AwYFCCw4NmprBNaOeTHH5z57B9q1biAiTAk+sy9Ko6o5bH0N8V0J2C7slhg8TTwqYcHbrAZxQjygPm+Rr2IPmbmpWAegHMCO3p4H92t4XYwn4EAvBKqNRv+26pk065dRy0C2wAMOqU8enZmUb7OseQCux87EajzBDg+l0iumMUF99DqPRGp587O3Y3LgvpCtbrr7lsrfEc2nEfmEZK16gkiY6a491GHgOG2mmPMV3d5/HtdF10IiAGuFdBWagYgZz1T4xQIVWXQGoK+ze3salb/w53vi278P65mbuzjZUhbUhKfy6Sj0I+ImeAg0HISAQTm2ewZkT5/OXdI6CWpwK/Tssb9oz85Y3VVOh4go1N63AUup70vME6ClTVuYK6TjBjaOfd4ygmtt9ZW6A5A7NLgYsJlndW2l70EoAw2htjJMXz+H6pSuY1TXqpsEzl5/Czt4dvOVN78R9J+5375XnPUSZUJXu03MWOP3PoWrHFPADy4y79Tae3fsObsxu4P4z53Bx8gZceum7mE6nwexoakIzqtvfmlHXhLphrLk15fWXXgXoG3jDD7wZGydOuKpT96gwHLJxl3rWr2HD0wkPENKfIiboyc378eDphzGq+p29MI/8Gn5fOyUFKCx6VkOvvAyM9sZotqZAzfGsBifYXrvKpzsAkreXdfEJnslJ1qhZWIl0CvulViedT25pqPLwyL8u1EjXk1YCGECEM6+7gGp9DVefv4ztvSn2mgZ7rz6Pnckuvv97fhhnzzzoksZWym3U0gKw0DH9sKefATqRgvdQS3Q4Xptew7N7z2Kn2QGDUVUVLj74CEajMb774rOY7O2BawaI0TSE2YxRTRuMxxVmM8ZsjTGbMdbWK1x94RXUsxke/UtvwdYpy6T3qrTEpwMIZrd5KoKEfEIhJ/jZrfN44PRFjEZdb1H2WdyK1KLzLZDoK+gk8ovMg62IeZbzaNoC4nRzCqoZPEI0+d3anpUlkdWhKmH/yFFnIERhrhEPoa5aAEDj4oWVYH5IG+k4hijppPFz3DMu5WGg02A1gAEAKsKp8/djvDbGK89fwt6dHUynNXauvYg73/gcfuBNP4SLF96I8WgcUCAbMEYGkuGeVcIeJPX2tJng8uRlXJpewpSnSToiwoPnX4dR1YLD3bt3wXW78QhozcR6xqBJ026TXquwtl5hc6tB/cKrmE2+ije+7S04cf+ZKEB+YMkLlmxMC2ze+vZ+htbJifDoMvQJAxWNcO7EBVw49RCqatR+BbnYD8PsTr9USRQY82BFZYKCCO9tRYjlRSnPaDoCKsa0mjqhccqihIliYpl+a0nSKtBCKsISKwQqvlSepd8oTxuCqpT9vrQ6wOA43zp9Eo987xO4fuUqrr18Bbe3d3H3xmVc+erv4PEHnsBffOytOHf6wXZym194RqJlZF/2taz8RGcAM57h2uwaLk8v405zJwi7JiLChXMP4L6t+3Dp8ot45ZWXMZlO2kproBYLWgJQjQnbdyqsrY9w59YV3L6+jYff/EY89MSjWNtYjwxTBIV8cFup98uHpm7a3yYuIYiBE2sncP7kQzi5dQqEyglOPCw2k4UEhIy2ht+Uo9JibuHHmrJO0hI2rByLh9HeGAxgujUFKlefOPwqaG4v/NlHZUW8FmgNBPJa/rlyeeTwXpWTWMKl8nIDN5bTdYR+B60EMHDToNnb9neoGDh3/iROnlzDay+/iquv3sT1vbu4+eLX8O0r38GTF/8Cvu/Rt+LcqfPZq8yhTHUhdEjRZ+O/AggwZvUUr21fxks738Ht+haYGFVi0qVbkL2WWmPGo+dO4/SoxqVXr2Jnb5I4BMMsaoBmwphOa8x2auzcvIHrl27j5Ucv44m3P4mzr38AVFXxfX+lkclZCsQMato/1Axq3BxngEA4XW3g7HgL48k2ZpPtaHkI4IyFRuEjHSxAxPtmeTIDxKnSmZUWZunw5UDClvbCDSwvHCuPHCDGkzFAjOnmLFmiZRaBNWn0tU+n2M3SVyrOa3UDTKxlBSEudUyfgweEkqXRg1YCGMaY4WzzWvI4jZnBBJx73Rh7Z89g1jTBhCN6Ds/duAoeP4nT9z3gvnYEIdbRRvAfbAUQ1hNx+sd0ctnAXOPm9Apu1VdwcqPGmYowHlVYG1eJszNYFsL9z760C6fRPH6q3fWYwU4kuTrwAjt+6VVs7e1htLEeUmRz0ZvZdYN6OsNsfYTZ68+hqRv3EiG7V4XbmeNONAvXvvUMBKduuyzxH3pp9140DoAYbk+Gu68bBqoZLpxex2Q6SjS8OJks2QfiGywtOHLp27nMDtAGD9diAAAcBElEQVTafshPScr7LTwpEgUn6QlC3lML04PueLqOERH2qgmaklUgybKopBPTh5eAQafx+90qI62RP/SfZaWIMH/GKel0Pag3MBDRCMAXAVxi5vcQ0eMAPgbgPIAvAfj7zDwhog0Avw7gLwO4CuCnmfm5rrI3N0Z48+NnhXDH3vMNa0P0w7UrIHpV8Ih8wGQb3H/+NOp2HUzxQzZCK26cYTyIU3Fnc+IxTyuIHmn2Fch+M/kIisX9l4SF8CbE6faEckdjYH0M3LcpOeowR9PZRn7WkLoXuZMNXu1V69doGvy1+vVoGgGOQHR8hmv/GNc9PXEgHxylTqgZEGWFqkL9TVKm50MIinS8hrwGP6Itkodvv3IVf/DcFdSWY1pbBvLaC7ccxNI81FaBNLMqFVeq3wIEo2yH/+F3CA2xGH4OwLcAnHb3vwTg3zHzx4jo1wD8LIBfdb/Xmfl7iOh9Lt1PdxU8qiqcOrmVWodKtYpXD4SWLbeWjJuolOfky/wTtlc9pNJCmCWkcnzgjbIEpMpOUhYKovS/Au8kwI1SHlRaL8hNw5jNakxnNSaTGXb3pu5vgt29KaazGnVdo+H2Oxd107SbvZqmFcTGWxx+Q1YU7rphVSeHzk9k1CsIAQqed7m68IJeuYCmSfvAAw2BkuVgPa1xbryO1/b2cmHSAp93vU0a8Uld+98a0WKw5KCUT9dfApCDeCpBRI8A+FsA/jWAn6e2l38MwN9zST4K4F+iBYafdNcA8N8A/AciIu7Y3F5VhK2tDbUnwYboTqEOkz3Nr+REBKbBEhSScrOLGGALqc6bC73IbebX7Yxz0qozhkUBcTmcPUk6PWkbCQYotLs2UbfLKwa177XMGuy5v8mMMZk1mM4aTKYOOKZ1+xGcuo7bw5v4FqhfngDt3otE3uT4OAGX2j9GRSuDhaWW790Qn9BR1kXTXsQlE4D7qjHuYobtuu4WUsnvPGCQ6XR6WYcEB51f3/cJl4ByQBbDLwP4BQCn3P15ADeYw4cOXwTwsLt+GMALAMDMMyK66dK/Jgskog8A+AAAnDu9hfWNNfip6jVGMmm9WMxxOqUWRXejSmUFgPBYJpAhw5diHVqD96tbJIhynQi2AJMgD1YFpXDZqxqYqB9viNoezv8Q3+6M74vUtQeIJlgbUwce3vKYTGtMpjNMZjVmM29pNJi5pyx147aUy/dQmIM10vh4hgAev2RpF6aVAyNvbrSLHvE0hxlNg2DJnF1fw9qUMG0YDdpNUN4KMZcoRncFi0NZPCbJ8NIr2CXBL8X5e/83z2+iaC4wENF7AFxh5i8R0buGFV8mZv4wgA8DwOOvP8tr445deJmmnU/a+96dprucVjC7yvGJbO60TJuCDjF+QdnnDffHdXVZOlmc5MmqV6/hFPbYrYKI5fQ2mCjC0oN3vspOj4Lm80W8iX4JCCvDCzI33L6f0kSA8MsYHzarW0Dx4OStmFndYCqAaDZr7z0IzWZpvmnTYDpt4305U18+M2Z1Ck6N47f2vhS04bUHLiACF0Ufh19RNd7qobiUZbfpIfi5RVez3HotRl7vUxmCDX0shh8B8BNE9G4Am2h9DL8C4H4iGjur4REAl1z6SwDeAOBFIhoDOIPWCVkmIoxGDhgKs3H+JIUQqCh88yw9wUJ36VJYDNM8W75QF7+xMLNdIXNWUW4FdABMWFaaoEYqSna2RzAEx29KmmNnOZDHA58pHYDssSPI8egTsJq9BHcEc4H7As03ePLb5AlI6iyVT8oaCU4sl0ntPmYZHvMhzQcXH6wV6Xfxb+dGB20AG2Ex+TrZLYMaFR4tqNb6YjA+8Zmn5nRMpLnAwMwfAvAhAHAWwz9l5p8hok8AeC/aJxPvB/BJl+VT7v4PXPznu/wLQDuO1ahK7s3poFWhmp99AECXZedJ7PQY4oNyeXW6MGVQGhBmPS4BKaSh9L9yIU4IE14Stm0Q0VaHRNAEeOYhcBIkcurPtYe22NMgWjwWv5qJHkCRm1Nm4oBdfsVoTrg4luyvveJJk/QgAcbByOLQd8F6UsM9361R7luZfqnA0EH/DMDHiOgXAXwZwEdc+EcA/AYRPQ3gGoD3zS2JWgekbCBlnSik0tvblQhPiwsmmCkgMkiCjJpdmRxKOVXSmLrxumdJ/FaBnwGppZEyWCjDx2tvs5YQMWdk2VmPVfIuxubWDCJC9iFTYjuSVaU0vs7+8E9FT7xqvRxXo6/ilT1OVHlwiULuOc5rSwPTQ3goSazUQs69pTxCzX1mYpkGAQMz/z6A33fX3wHwDiPNLoCfGlIugcT3DMRkthA8s23tF4ejFiqVJRPCHJBwY1jOcnR6vbqsklSoMozPZWh+uXpPhVminvjBMrDBSWYiAdThMR/JjkBY/0aeYr9Lb4L9+LUvpZqanY7oCzx6HIsat295unhq+0HmIOOqJcMsKNam0GoOJreptVItl16ildj5CACkNUXWw3EiW7IKiMmny1hEuaVVGvxY+eeMGGBMzjzC5KN3I8jQeqKgpE9iw+IkEsCs8hDkxHTeMQCUSKiAOwFAfcBTDjMn/EtNnS/TSmXJ5qTFWDNICGqXRZTLs+DNKj+/9Ux1wAUCCvapWJXRJpP5h6Px6gCD6SCzBigVpzgdGVViV4t1e+fiLe08WyhLTBdYDNGUTj/qyqORJx9UX8a8pySJAGR4W4JVylmYW3ZcqsUtyVLAhCb1Q8E89ylOy0ppiShBwveFUBmhXKvkPg1UbZB1s8UR0DVPldkUKeJqSJ2UwPJCg3WZ/RisKhsIDqsBDARlnloDyIhH4mQQbGgksdYjFZ8U72dVXmY3y+7xG6Xl6vluOtWT56ScAEiILvaBcDYKtRgMfSrpZsknKWyIoJhpLU+cXeQ1FGRDNjf019y9EilPSXnecSciyPNWAps+RN3Z5+1ZMYOt8zQEBufGSWEedk1NUUbJRug/s1taDWBAO2GyAz2Y5CxN7cskTpAhiEXlR0GuhIiKTHMsMUsE49btHDgCa8mEoSSfpYViCKnuSLV2pzbT2k8UlOLkPFWkwMKp0tzlVsrfj6SeiEMhlxDW8mRBQBBU1q0DyvYMs7oXcypEUZ401tVDWbH4tYZmGOeBVgYYAGNSattKTk7xpmQmxJRmK5phYrWRVVcIaIuSWj493j1dsdiiapediWh2SSqcdKQ1h4yt1YXqO7V4XnxqV8clsUdZ3eH2BA8xSZ8pn0XANRk+cNrPkTHLOCr7RebUq+tRySWEztfkhXp6da+frcNpJYAhDDV1LT01HPY1C/yvHkyJCvZAK4tfhEuR7MeH9Oob9omR16q8rM3jG6Od8l3gt9wPunZ7/rmecGDNUtKTjG4Z5OxnTnqkBIpdjVnQQlDYJa1V+YLVsuqV+9VAog8TJTK83EDaavBWidhPMrTklQAGQAgb6WloTFo/sJmfIVK+dCM1q6WmTUZHMWYUbiQpGCTJBPNfRArCOFfhGZWTvJPbjH0dPbiUDCYpyAouiGwsz2u+DEQI0R8A6RvxYjBQ6/ehEnoJxnRtyfkdy6irUHXWQR3TbmGyrBUA2aazObQiwCCnm5yc0oFIUemHZbOY4YkVURjgeVbFAH6DomUt/uge8IJilCVLwJunsfvtoaDYPwIbSnhotQWsa7e0kVtgectFRA523C1M2rzTYIYQT9qRMZSfLlmzDKZSfsPxnT16X4Q4DvnQ5cSKAEM+cczJWtTeWg2UbIfcJDftEiu7yJp4kud617vItobi/gAU/CA9zRf5LDzruzahuZxJuskzEVS/4LE83fbVLfui6JPwLxwhLBVSiM2FrzRvBpDsFk5+EivB30tFeBBd1v0yQplWBhiMGemo7GXJ9oBAgK9XksnDYjKL6+WAVMUsg+JzeFcg5/yUGTKCDUBo1812rsxpChhDIDosX58JCdT8LTgj90thfR1ZYbEBIcH0ZHD1Qn3BQbb60fAB5OdtdNpt+6NuDDdphYDBdY7oj9ZhQ1Gek8eZhjmYlYe8fw+h/61xaHkht+qJ7SgaOmbp5aj2iDqxVqZcE6VyLe6K6koBtAYsaTpljV4uQFhKwEwjWA2LPIp8lP0aRXN0qZSOk+crr3P5XAwrcaWAwbJq5bzrVqVSpZfEc7nkNyKxMNflNz/Mpx7CfIwJizUgmziGYZU/FqUkeXrdsXToZMqw4ojyqKTMjv4fODwSFOSOR3D0lYS3XzPQ1er7YIU/ITVW8dhhy0eDfC/P0ngYJgsr81Hb5fVF0SbuwUM5rdy4RESQh6aGe++g8H8xd28ecs0lhNwpP1+15yA+YrNMUk1+vWJWkdZXymvGqWTzUhXmKZk85fHZbneO/RP51HOgBAqHsOwJ3U7JOMnxA9I5mJ5dfri0MsCwPBSnDgGn8M/fJeQHLjw6TUGA4swrFL+MNni1F4vMcAaWJaBDSyQkqiScoiRSifNHmmqDly5Lr6WpO46NtHrzEQPuEBM4C0H3gfyzWpW2YOkWhK5K1uoPf4HfJEciXPZqdiLn4rwsQKsDDMY46vcQOrML4fEOPf+9ifC/mO1eyFMLQJY30NZdgJLvcOq2Dqp64OgH06NvSTJx/ii4vLdOHQUPSpYE1vk9wSISqxX5YIVkGskvybLndd4BLic87wp3SDAc/T8ioWuYO0FzeVNvwXJWw8cQED9Cf+tJ5rQTyQt5ubWZPGcTKK/bvLYDlkqJhpDHCKklfJl68jdnqzPQPX+s3JaVkgFEWF5xMPWt5W4KwoXxNYK9jyctR4ZZAKDdsTDS7INMrzPUkxEOaf1uS304TrIXDnZLDpJWxmLI+lOs4YG4COgFgYfZgx3Vdhk8RMKqCU4DCtpweaDgfgvaOS4Q+hw4k8dHjw4nmjxdi3jAdwfgJcsJLyiUZqKUZfnEKm9KaU50gYKPP2DLUFoPxvItHIMvz5xMFmqR08OklQGGxRquZ+HRUEnrJnsU/A9Rpuna8CGtGAIKoWKzhGiPGbPWrMYqR31XUzRZhjPUrk7KU/g/Quw7Ih8ny1dAkkmgpq64g5k/GiSDMjATJy3MoPKwHZArAwzDSE8oGXZAgzww0hSU4npmKCdq0S2j9GTsWRtZfA2wXwsWtLiPJgCLBO1nAnUu3ah5NRoWh0kHNz8s0mctJN+m8OyINJG7FKR9r8l/wMGCxWr4GAaRBQiHUy0B5vN0ePM42X5M7enP81937Fc5gMSw7JAd7d3vN4EKPGZLcrs0y2j34UFcs37IvwOaSUvme5Cmf1fLrGXDEsmxkWy80qsSa5ViIGjXPhRZTOdr/EumlbUYFpIlssxMK1l34dZjMq2k0zTCW9gbt/rivZ5dbF7qkr3PoJ/hPKezEwVmpc37e7huNjzG2b38LUFRqYwlk/cfqqFJ/EOWg4DEkkI41q0nO9ZmqMOilQEGv/aWjxzzREg62VBAdrjLHJ/B63VuXny6gclfUjLybAqLT8wi437WtVI7Cg4Ljvs4JzmEWfGdROJvnvdsX1TS6LKeUv/5uHnLh4MnudfEf3kqYSnMy64DCCPpMyH2/ZblArQywNBSKowJ+lLy068oSK+/62zv0BLXPrxbfA09m5nBJa23z4G1QErIhIhNrAVZeycHWr4yC6GP8C0KGFq96jrn1evjl6tVh1isYbNVorWQAILG8/DtTMRHlan/IPUjHDY4rBgwAHHd6e+E2e7CJGBkj76UDyBex8HxIOAfEWmvd6y55B/o0mD7pETy7VLLtQw8aMSX1naGVZxhvZdqWNbEnfd0oUTLB4dBVXcEcTYuaoIjh9+l7HrcB60QMGhPawqxpngusrT38cqSSDFZC6dVWm/DfBj5QwSCEPodfay7pNdKu3N9mi0VjIIz90aX8C3SH3ohLiuW132WMcsbjz7nGAQFFdJytsHO3/vvUCZ2ULIDMuNgEbaXRisEDC2lONn13oNS5oYF0b9GaZP3KeBgcTysRUWbis+/DUrf3OvIpc+qaDOXCi0wOzdgDvUB3T5LmeXTvKkg39eQ99JyTbpNDGqLFzE29QgdkNIZQCsEDEfbES0dDg/zht10YBllWKVKM3Q+CZPLb9ktyaMVl1nvy3ZOSlr+2PQR/KTqjrEoLX/belqTlkSK0jOU3rt7D5hWCBg8afOxFH/v0rynf3JPRLpWTQ1su9QF+6ckJdkajSIgHP383ReZp3+ZCdUv0Aq6sBSQRsU3P0WYL0QuXltLUKLsUTyczGkFgWEe7WPyHzHZRnNJICmbcWVLw1Lp+2Cqi7w5QzCqvTfHxVMvgVRNzJaz5MohARAojaMHghTU0zlxNDCxOsBgrlXnQfi9RUFTCN+B9eox4M3TgUuCvtQ175J1TCHvXLbuUYAw2p09/UqsB0rTILZcYmVu+8XIdC/M6ii91QGGuR5vT6vRcX3InAoJKOi4bmfrvivvk0Y+1s0i9aK7RCsO3Av4R73fwNzxqhJTcu13oNpPHqJTebX6bHWAAUB5xCQWr1YHWqQ5TZXsHE/WQrUZZfV5ipA5DucVIVtGaQKpIpcFbssgSgUawHDX1dwpl3oQotEVH7Pap0AT5vsUjqYvVwwYChTmvl7Q6bDlVzsofcmR6P6kU9Ef+kkhblnt6AmcgS/dj329iowMAfdDBzWMnFtmQDpWfq9B3yHwL6ml5VL4P99X45cJgaXkisT/q0KrAwwWoMrfZIF+OM6ZviV3vt+RJRbPuMNXrNL2DPNLa5d5yZmpsgT510AQNdkgkskX+crJARuCpR2xMi57hKjmYNZLoZzUecjqL80lUwmtISsyuZkXvlzqBQxE9BwRfY2I/pSIvujCzhHRZ4no2+73rAsnIvr3RPQ0EX2ViN7ei5PMCeb+072rUXofmnY/GG2+RSfKTF6qUf681LTNn2gP2xe/gOXUa2VmgYOQIAtLVoz01JBjklgI2nrQ5WBYE+30lubrss66ltX9adFhGWIx/FVmfisz/6C7/yCAzzHzkwA+5+4B4G8CeNL9fQDAr/Yq3QRPw7zVLWUrsB95h1JgYcFelLpaDrW9ZVtcdb59OaR2Wz9lVZIKDGrPnqSU9T/FcopsH40PyBo72f/+XtpX2VEZKr1VlkuBsqCX4MCy6LoQejn9uGgp+1lK/CSAj7rrjwL42yL817mlPwRwPxFdnFcYAcn8C2s1eWFORkt99aMMY6R1Z6W3tImhleR1+vShpIX3q26H6jSZbwiJNXHXjNNjdgjUtXqxzkww+RIAko01yYu0Mhb/q8RJimFiusSOW6CovsDAAH6XiL5ERB9wYQ8x82V3/TKAh9z1wwBeEHlfdGEpr0QfIKIvEtEXb93ZFRFppaxu9MuH8hsQMaGMLw+yuabUZqagbPKJtF2Wh22J7NdSkOUgH/y5kyEKOSUZovURdRzlOV3GzMCzpG4Zc3yJmGfqFn9ZGPuuZYHsv3SzUmYCdzB3SAjak/oe7fajzHyJiB4E8Fki+jMZycxMRINmOTN/GMCHAeDJRy+wNSCJqAs5SkSKLXDwUdF2JDdzwxtuhlxq01Ne649Gh0j7rDdjnPtOkHlUmLWaDSO8DcrPneAk1gr3Me2Etw6BsdihzLeSgjfHy9h1BctaNiWUT7EM+bqH7mo5t8Qp7kq55OOW2nJ9xqrkHbLG/hBpAf3Ty2Jg5kvu9wqA3wbwDgCv+CWC+73ikl8C8AaR/REX1kny5T7psNNOuwgITqsRizwcv+gjAIBDco6V+DglUECsP1QF2/LgZJa5lEWLngvXQ8nwJwRmOb01c8v8+enQ6VVME1NGUDA3SbI4YsTor/AlplITSnyrJUDXk4VkDjnpDnrcYUC2GJDpHSUg6ecbx35RHBT+dJzOY93PS3fwNBcYiOg+IjrlrwH8dQBfB/ApAO93yd4P4JPu+lMA/oF7OvFOADfFksMkrX/k8lT+SQSPX5ry32LgGOYysAAS/YabPHEnWMC6bldpaiX4bJRNzjRRlqEQP4dMZSN7pJUY08MOkaxQq/5eB2Ux8pN+qmWUctL2GSXp0lOy7D+rvHyXoWoTovbPytRhmncxD2TB5rJT8KZ56SbL9BFjlqTx6fQgWuk6quqMGwYufZYSDwH4bTfAYwC/ycy/Q0R/DODjRPSzAJ4H8Hdc+v8J4N0AngawDeAf9mGk3fDjrrvSIZnrIoMWRmGj+nxMyREE8bVa9cVqGeYmuvUVYvndiGA9MCF+eUnUrUYvNVPnNBiu3IxihwWxFkrH1Duh4sibLKvc92l8sApEQ6I1Jy8idPSxCmJVcQzjvo9CHj0hAlKRH/hUxlweLZZttP8ylA8n9789fua8CNVYSwt71GVayUsvSochjQoDNupXlq+79BLPYRIR3Qbw1FHz0ZMuAHjtqJnoQfcKn8C9w+u9widg8/pGZn6gT+ZV+a7EU2J/xEoTEX3xXuD1XuETuHd4vVf4BPbP6+psiT6mYzqmlaFjYDimYzqmjFYFGD581AwMoHuF13uFT+De4fVe4RPYJ68r4Xw8pmM6ptWiVbEYjumYjmmF6BgYjumYjimjIwcGIvobRPSUO7/hg/NzHCgv/5mIrhDR10XYcs+dWB6vbyCi3yOibxLRN4jo51aRXyLaJKI/IqKvOD7/lQt/nIi+4Pj5LSJad+Eb7v5pF//YYfAp+B0R0ZeJ6NMrzudzdJBnpMj3Cw77D8AIwDMAngCwDuArAN5yhPz8FQBvB/B1EfZvAHzQXX8QwC+563cD+F9oN5y9E8AXDpnXiwDe7q5PAfhzAG9ZNX5dfSfd9RqAL7j6Pw7gfS781wD8I3f9jwH8mrt+H4DfOuR+/XkAvwng0+5+Vfl8DsAFFba0sT+0hhQa98MAPiPuPwTgQ0fM02MKGJ4CcNFdX0S7GQsA/hOAv2ulOyK+Pwngx1eZXwAnAPwJgB9CuytvrOcBgM8A+GF3PXbp6JD4ewTtoUM/BuDTTpBWjk9XpwUMSxv7o15K9Dq74YhpX+dOHAY5M/ZtaLXxyvHrzPM/RfsG7mfRWok3mHlm8BL4dPE3AZw/DD4B/DKAXwDQuPvzK8on0L4esdQzUiStypboe4KYh587cdBERCcB/HcA/4SZb8kXelaFX2auAbyViO5H+9r+9x4xSxkR0XsAXGHmLxHRu46anx609DNSJB21xbDQ2Q2HTEs9d2KZRERraEHhvzDz/3DBK8svM98A8HtoTfL7icgrJslL4NPFnwFw9RDY+xEAP0FEzwH4GNrlxK+sIJ8AAD7gM1KOGhj+GMCTzvO7jtaJ86kj5knT0s6dWCZRaxp8BMC3mPnfriq/RPSAsxRARFto/SDfQgsQ7y3w6fl/L4DPs1sYHyQx84eY+RFmfgztPPw8M//MqvEJ4FDOSDkSR5lymLwbrUf9GQD//Ih5+a8ALgOYol2H/SzadePnAHwbwP8GcM6lJQD/0fH9NQA/eMi8/ijadeZXAfyp+3v3qvEL4AcAfNnx+XUA/8KFPwHgj9Ce2/EJABsufNPdP+3inziCefAuxKcSK8en4+kr7u8bXm6WOfbHW6KP6ZiOKaOjXkoc0zEd0wrSMTAc0zEdU0bHwHBMx3RMGR0DwzEd0zFldAwMx3RMx5TRMTAc0zEdU0bHwHBMx3RMGf1/lC32frvaPnQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": [],
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": [],
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": [],
      "needs_background": "light"
     }
    }
   ]
  }
 ]
}